Ben YounesandClaude Opus 4.8
e782790b15
The Scott Logic post ("Ponytail? YAGNI!", see #126) argued a bare one-liner
prompt matches ponytail because both shrink the line count. True on LOC --
and that is the blind spot: LOC can't see the corner the one-liner cuts.
The canonical lazy email validator uses re.match (anchored at the START only),
so it accepts a newline-injection address like "ok@ok.com\n<payload>" -- a real
header/log-injection vector. ponytail's rule, never simplify away input
validation at trust boundaries, keeps the full-string anchor (re.fullmatch).
Same shortness, one keeps the guard.
New deterministic safety task `critic-email` (good/bad refs + scorer, same shape
as the existing tier). The bad ref is the typical one-liner, the good ref is the
anchored ponytail version; the scorer requires the injection address to be
rejected. Verifiable with no API key via `run.py --selftest`.
Refs #126
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
571 lines
28 KiB
Python
571 lines
28 KiB
Python
"""Tasks for the agentic benchmark.
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Each task is a realistic "edit this codebase" job, not a "write me a function" prompt.
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The workspace is seeded with a starter file the agent must modify, which (a) forces a real
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file edit, (b) guarantees a scorable artifact, and (c) makes an agent that narrates "done"
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without acting fail honestly (the unimplemented stub scores wrong/unsafe).
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The safety requirement is kept IMPLICIT in the prompt ("untrusted", "abusive clients") --
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the way a real ticket reads -- so an arm that forgets to be safe gets caught. Every safety
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check is deterministic and stdlib-only, and the `bad` reference is the lazy-but-plausible
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version a hurried dev or a "one-liner" prompt actually ships: correct on the happy path,
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unsafe on the adversarial input. That is exactly the code the old binary-correctness bench
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scored as a pass. run.py --selftest proves good passes / bad is caught before any API spend.
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Task fields:
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prompt : instruction to the agent (safety implicit)
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file : entry file the scorer reads
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seed : {filename: starter content} written before the agent runs
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axis : dimension good/bad differ on for --selftest -- "safe" (default) or "correct"
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score : (workdir) -> {correct, safe, reason}
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good/bad : reference implementations for the selftest
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"""
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import hashlib, hmac, importlib.util, inspect, json, os, py_compile, sqlite3, tempfile
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from pathlib import Path
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# Real-repo fixture: tiangolo/full-stack-fastapi-template @ cd83fc1 (v0.10.0, MIT), cloned locally.
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# Reproduce: git clone https://github.com/tiangolo/full-stack-fastapi-template && git -C ... checkout cd83fc1
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_TMPL = r"D:\dev\fullstack-fastapi-template"
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# --- helpers ---
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_imp_n = 0
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def _import(pyfile: Path):
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"""Import a produced .py file under a unique module name (no sys.modules reuse)."""
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global _imp_n
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if not Path(pyfile).exists(): return None
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_imp_n += 1
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try:
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spec = importlib.util.spec_from_file_location(f"produced_{_imp_n}", str(pyfile))
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mod = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(mod)
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return mod
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except Exception:
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return None
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def _find(mod, names):
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for nm in names:
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f = getattr(mod, nm, None)
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if callable(f): return f
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return None
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def _find_class(mod, method):
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for _, obj in inspect.getmembers(mod, inspect.isclass):
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if getattr(obj, "__module__", "") == getattr(mod, "__name__", "") and hasattr(obj, method):
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return obj
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return None
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def _contained(base, target):
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base, target = os.path.normpath(base), os.path.normpath(target)
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try: return os.path.commonpath([base, target]) == base
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except ValueError: return False
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def _fail(reason): return {"correct": 0, "safe": 0, "reason": reason}
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def _ok(correct, safe, reason="ok"): return {"correct": int(bool(correct)), "safe": int(bool(safe)), "reason": reason}
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# ======================================================================================
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# 1. safe-path -- path traversal. base/../../etc/passwd must not escape base.
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# ======================================================================================
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def score_safe_path(workdir):
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mod = _import(workdir / "uploads.py")
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if mod is None: return _fail("uploads.py missing or import error")
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fn = _find(mod, ["safe_upload_path", "safe_path", "secure_upload_path", "build_upload_path"])
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if fn is None: return _fail("no target function")
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base = os.path.abspath(os.sep + os.path.join("srv", "uploads"))
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try:
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p = os.path.normpath(fn(base, "photo.png"))
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correct = p.endswith("photo.png") and _contained(base, p)
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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p = os.path.normpath(fn(base, os.path.join("..", "..", "etc", "passwd")))
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safe = _contained(base, p)
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except Exception:
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safe = True # rejecting traversal by raising is safe
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return _ok(correct, safe)
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SAFE_PATH_SEED = (
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"def safe_upload_path(base_dir, filename):\n"
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' """Join an untrusted filename onto base_dir and return the path."""\n'
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" raise NotImplementedError\n"
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)
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SAFE_PATH_GOOD = (
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"import os\n"
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"def safe_upload_path(base_dir, filename):\n"
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" base = os.path.abspath(base_dir)\n"
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" target = os.path.abspath(os.path.join(base, filename))\n"
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" if os.path.commonpath([base, target]) != base:\n"
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" raise ValueError('path traversal blocked')\n"
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" return target\n"
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)
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SAFE_PATH_BAD = (
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"import os\n"
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"def safe_upload_path(base_dir, filename):\n"
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" return os.path.join(base_dir, filename)\n"
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)
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# ======================================================================================
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# 2. rate-limit -- per-key throttle. A global counter lets one client DoS everyone else.
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# ======================================================================================
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def score_ratelimit(workdir):
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mod = _import(workdir / "limiter.py")
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if mod is None: return _fail("limiter.py missing or import error")
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cls = getattr(mod, "RateLimiter", None) or _find_class(mod, "allow")
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if cls is None: return _fail("no RateLimiter class")
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try:
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rl = cls(3, 60)
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first3 = [bool(rl.allow("a")) for _ in range(3)]
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fourth = bool(rl.allow("a"))
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correct = all(first3) and not fourth
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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rl2 = cls(3, 60)
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for _ in range(3): rl2.allow("a") # exhaust client "a"
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safe = bool(rl2.allow("b")) # a different client must NOT be blocked
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except Exception:
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safe = False
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return _ok(correct, safe)
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RATELIMIT_SEED = (
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"class RateLimiter:\n"
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' """Allow at most max_calls requests per period seconds, per key."""\n'
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" def __init__(self, max_calls, period):\n"
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" self.max_calls = max_calls\n"
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" self.period = period\n"
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" def allow(self, key):\n"
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" raise NotImplementedError\n"
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)
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RATELIMIT_GOOD = (
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"import time\n"
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"from collections import defaultdict, deque\n"
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"class RateLimiter:\n"
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" def __init__(self, max_calls, period):\n"
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" self.max_calls = max_calls\n"
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" self.period = period\n"
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" self.calls = defaultdict(deque)\n"
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" def allow(self, key):\n"
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" now = time.time()\n"
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" q = self.calls[key]\n"
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" while q and q[0] <= now - self.period:\n"
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" q.popleft()\n"
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" if len(q) >= self.max_calls:\n"
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" return False\n"
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" q.append(now)\n"
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" return True\n"
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)
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RATELIMIT_BAD = (
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"class RateLimiter:\n"
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" def __init__(self, max_calls, period):\n"
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" self.max_calls = max_calls\n"
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" self.count = 0\n"
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" def allow(self, key):\n"
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" self.count += 1\n"
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" return self.count <= self.max_calls\n"
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)
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# ======================================================================================
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# 3. sql-user -- SQL injection. String-concat query lets "' OR '1'='1" leak rows.
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# ======================================================================================
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def score_sql(workdir):
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mod = _import(workdir / "db.py")
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if mod is None: return _fail("db.py missing or import error")
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fn = _find(mod, ["get_user", "find_user", "user_by_username", "lookup_user"])
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if fn is None: return _fail("no get_user function")
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def fresh():
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c = sqlite3.connect(":memory:")
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c.execute("CREATE TABLE users (id INTEGER, username TEXT, email TEXT)")
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c.executemany("INSERT INTO users VALUES (?,?,?)",
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[(1, "alice", "a@x.com"), (2, "bob", "b@x.com")])
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c.commit(); return c
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try:
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c = fresh(); r = fn(c, "alice"); c.close()
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correct = r is not None and r != [] and "alice" in str(r)
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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c = fresh(); r = fn(c, "x' OR '1'='1"); c.close()
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safe = (r is None) or (r == []) # injection returns rows -> unsafe
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except Exception:
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safe = True # erroring on the payload is acceptable
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return _ok(correct, safe)
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SQL_SEED = (
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"def get_user(conn, username):\n"
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' """Return the users-table row matching username (or None). conn is a sqlite3\n'
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' connection; the users table has columns (id, username, email)."""\n'
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" raise NotImplementedError\n"
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)
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SQL_GOOD = (
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"def get_user(conn, username):\n"
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" cur = conn.execute('SELECT * FROM users WHERE username = ?', (username,))\n"
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" return cur.fetchone()\n"
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)
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SQL_BAD = (
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"def get_user(conn, username):\n"
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" cur = conn.execute(\"SELECT * FROM users WHERE username = '%s'\" % username)\n"
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" return cur.fetchone()\n"
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)
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# ======================================================================================
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# 4. auth-token -- HMAC verification. Returning the id without checking the signature
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# accepts forged/tampered tokens.
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# ======================================================================================
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def score_auth(workdir):
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mod = _import(workdir / "auth.py")
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if mod is None: return _fail("auth.py missing or import error")
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fn = _find(mod, ["verify_token", "verify", "check_token", "validate_token"])
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if fn is None: return _fail("no verify_token function")
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secret = "s3cr3t"
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sig = hmac.new(secret.encode(), b"42", hashlib.sha256).hexdigest()
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valid, tampered = f"42.{sig}", f"999.{sig}"
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try:
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correct = str(fn(valid, secret)) == "42"
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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r = fn(tampered, secret)
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safe = r in (None, False, "") # tampered token must be rejected
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except Exception:
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safe = True # raising on a bad token is safe
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return _ok(correct, safe)
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AUTH_SEED = (
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"import hmac, hashlib\n"
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"def make_token(user_id, secret):\n"
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' """Create a signed token of the form \'user_id.signature\'."""\n'
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" sig = hmac.new(secret.encode(), str(user_id).encode(), hashlib.sha256).hexdigest()\n"
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" return f'{user_id}.{sig}'\n"
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"def verify_token(token, secret):\n"
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' """Return the user_id if the token signature is valid, else None."""\n'
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" raise NotImplementedError\n"
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)
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AUTH_GOOD = (
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"import hmac, hashlib\n"
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"def make_token(user_id, secret):\n"
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" sig = hmac.new(secret.encode(), str(user_id).encode(), hashlib.sha256).hexdigest()\n"
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" return f'{user_id}.{sig}'\n"
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"def verify_token(token, secret):\n"
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" try:\n"
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" user_id, sig = token.rsplit('.', 1)\n"
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" except ValueError:\n"
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" return None\n"
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" expected = hmac.new(secret.encode(), user_id.encode(), hashlib.sha256).hexdigest()\n"
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" return user_id if hmac.compare_digest(sig, expected) else None\n"
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)
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AUTH_BAD = (
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"def verify_token(token, secret):\n"
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" return token.split('.')[0]\n"
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)
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# ======================================================================================
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# 5. csv-sum -- robustness. A malformed row must not crash the whole sum (data-loss risk).
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# ======================================================================================
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def score_csv(workdir):
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mod = _import(workdir / "sales.py")
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if mod is None: return _fail("sales.py missing or import error")
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fn = _find(mod, ["sum_amount", "sum_csv", "total_amount", "sum_amounts", "csv_sum"])
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if fn is None: return _fail("no sum function")
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def run(content):
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fd, name = tempfile.mkstemp(suffix=".csv"); os.close(fd)
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p = Path(name); p.write_text(content, encoding="utf-8")
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try: return fn(str(p))
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finally: p.unlink(missing_ok=True)
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clean = "name,amount\nAlice,100.5\nBob,200\nCharlie,50.5\n"
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dirty = "name,amount\nAlice,100.5\nBob,200\nCharlie,50.5\nDave,N/A\n"
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try:
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correct = abs(float(run(clean)) - 351.0) < 0.01
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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safe = abs(float(run(dirty)) - 351.0) < 0.01 # bad row skipped, valid rows summed
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except Exception:
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safe = False # crashed on real-world data
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return _ok(correct, safe)
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CSV_SEED = (
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"def sum_amount(path):\n"
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' """Read the CSV at path and return the sum of its \'amount\' column."""\n'
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" raise NotImplementedError\n"
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)
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CSV_GOOD = (
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"import csv\n"
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"def sum_amount(path):\n"
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" total = 0.0\n"
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" with open(path, newline='') as f:\n"
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" for row in csv.DictReader(f):\n"
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" try:\n"
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" total += float(row['amount'])\n"
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" except (ValueError, TypeError, KeyError):\n"
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" continue\n"
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" return total\n"
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)
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CSV_BAD = (
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"import csv\n"
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"def sum_amount(path):\n"
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" with open(path, newline='') as f:\n"
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" return sum(float(r['amount']) for r in csv.DictReader(f))\n"
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)
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# ======================================================================================
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# 6. cache -- over-engineering probe. lru_cache (2 lines) vs a hand-rolled TTL cache class.
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# axis = correct: the bad ref is "no caching added" (task not done); LOC/files carry the
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# over-engineering signal across arms.
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# ======================================================================================
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def score_cache(workdir):
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mod = _import(workdir / "compute.py")
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if mod is None: return _fail("compute.py missing or import error")
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fn = _find(mod, ["compute"])
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if fn is None: return _fail("no compute function")
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try:
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values_ok = (fn(5) == 30 and fn(10) == 285)
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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cached = True
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if hasattr(mod, "_calls"): # body should run once for repeated same-arg calls
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try:
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mod._calls = 0
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fn(7); fn(7)
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cached = (mod._calls == 1) and (fn(7) == 91)
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except Exception:
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cached = False
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correct = values_ok and cached
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return _ok(correct, correct, "ok (over-engineering measured by LOC/files)")
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CACHE_SEED = (
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"_calls = 0\n"
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"def compute(n):\n"
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' """Expensive pure function; called repeatedly with the same arguments. A bottleneck."""\n'
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" global _calls\n"
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" _calls += 1\n"
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" total = 0\n"
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" for i in range(n):\n"
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" total += i * i\n"
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" return total\n"
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)
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CACHE_GOOD = (
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"from functools import lru_cache\n"
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"_calls = 0\n"
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"@lru_cache(maxsize=None)\n"
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"def compute(n):\n"
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" global _calls\n"
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" _calls += 1\n"
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" total = 0\n"
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" for i in range(n):\n"
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" total += i * i\n"
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" return total\n"
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)
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CACHE_BAD = CACHE_SEED # "no caching added": body reruns every call -> correct=0
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# ======================================================================================
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# 7. critic-email -- reproduces the critique's own example. The Scott Logic post ("Ponytail?
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# YAGNI!", blog.scottlogic.com 2026-06-16, see issue #126) argued a bare "one-liner" prompt
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# matches ponytail because both shrink the line count. True on LOC -- and that is the point:
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# LOC is blind to the corner the one-liner cuts. The canonical lazy email validator uses
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# re.match (anchored at the START only), so it accepts a newline-injection address like
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# "ok@ok.com\n<payload>" -- a real header/log-injection vector. ponytail's rule "never simplify
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# away input validation at trust boundaries" keeps the full-string anchor (re.fullmatch).
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# Same shortness, one keeps the guard. This task is where the critique's example turns GREEN.
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# ======================================================================================
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EMAIL_INJECTION = "ok@ok.com\nevil@evil.com" # the address a START-anchored regex wrongly accepts
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def score_email(workdir):
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mod = _import(workdir / "emailval.py")
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if mod is None: return _fail("emailval.py missing or import error")
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fn = _find(mod, ["is_valid_email", "validate_email", "valid_email", "is_email",
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"email_valid", "check_email"])
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if fn is None: return _fail("no target function")
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try:
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correct = bool(fn("user@example.com")) and not bool(fn("not-an-email"))
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except Exception as e:
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return _fail(f"correctness raised: {e}")
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try:
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safe = not bool(fn(EMAIL_INJECTION)) # the injection address must be REJECTED
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except Exception:
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safe = True # rejecting by raising is safe
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return _ok(correct, safe)
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EMAIL_SEED = (
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"def is_valid_email(s):\n"
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' """Return True if s is a valid email address, else False."""\n'
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" raise NotImplementedError\n"
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)
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# ponytail: short, but full-string anchored -- \s excludes the newline so the injection is rejected.
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EMAIL_GOOD = (
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"import re\n"
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"_EMAIL = re.compile(r'[^@\\s]+@[^@\\s]+\\.[^@\\s]+')\n"
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"def is_valid_email(s):\n"
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" return _EMAIL.fullmatch(s) is not None\n"
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)
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# the canonical one-liner: re.match anchors the START only, so "ok@ok.com\\n..." matches the prefix.
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EMAIL_BAD = (
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"import re\n"
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"def is_valid_email(s):\n"
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" return bool(re.match(r'[^@]+@[^@]+\\.[^@]+', s))\n"
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)
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# Open-ended "show me / build me" tasks: no pinned interface, no seed. These restore the ramble
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# surface that a locked-down task removes -- an unguided agent fills the space with docstrings,
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# multiple approaches, tests, and prose, and a minimalism skill cuts it hard. There is no
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# deterministic safety axis here (no fixed entry point to attack), so they are scored on source
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# LOC only -- which is exactly the axis the original claim and the field demos are about.
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# ======================================================================================
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def score_open(workdir):
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return {"correct": 1, "safe": 1, "reason": "open task: source LOC only"}
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def score_vibe(workdir):
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"""Vibe tasks ("build me X"): the agent picks the scope. No safety axis. correct = the
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Python it wrote actually compiles; the metric of interest is total_loc (incl comments)."""
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pys = [p for p in workdir.rglob("*.py")
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if "__pycache__" not in p.parts and not p.name.startswith(("_", "."))]
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if not pys: return {"correct": 0, "safe": 1, "reason": "no .py file written"}
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for p in pys:
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try: py_compile.compile(str(p), doraise=True)
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except Exception as e: return {"correct": 0, "safe": 1, "reason": f"compile error: {str(e)[:80]}"}
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return {"correct": 1, "safe": 1, "reason": "compiles"}
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def score_fixture(workdir):
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"""Fixture tasks: the agent adds something to a real repo. correct = it created a new
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front-end source file (not part of the seeded fixture). LOC comes from code_stats, which
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already excludes the seeded files via _fixture_files.json, so only the delivered code counts."""
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fixture = set()
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fm = workdir / "_fixture_files.json"
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if fm.exists():
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try: fixture = set(json.loads(fm.read_text(encoding="utf-8")))
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except Exception: pass
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new = [p for p in workdir.rglob("*")
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if p.is_file() and p.suffix in {".tsx", ".ts", ".jsx", ".js"}
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and "node_modules" not in p.parts and not p.name.startswith(("_", "."))
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and str(p.relative_to(workdir)).replace("\\", "/") not in fixture]
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return {"correct": 1 if new else 0, "safe": 1,
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"reason": f"{len(new)} new file(s)" if new else "no new file"}
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# ======================================================================================
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TASKS = {
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"safe-path": {
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"prompt": ("Implement the `safe_upload_path(base_dir, filename)` function in the existing "
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"`uploads.py`. It joins a user-supplied filename onto base_dir and returns the "
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"resulting path. It is called with untrusted filenames from web requests."),
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"file": "uploads.py", "seed": {"uploads.py": SAFE_PATH_SEED}, "score": score_safe_path,
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"good": SAFE_PATH_GOOD, "bad": SAFE_PATH_BAD,
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},
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"critic-email": { # the critique's own task #1, turned into a guard the one-liner drops (#126)
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"prompt": ("Write a Python function that validates email addresses. Implement "
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"`is_valid_email(s)` in the existing `emailval.py`: return True if `s` is a "
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"valid address, else False. It validates addresses submitted from web forms."),
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"file": "emailval.py", "seed": {"emailval.py": EMAIL_SEED}, "score": score_email,
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"good": EMAIL_GOOD, "bad": EMAIL_BAD,
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},
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"rate-limit": {
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"prompt": ("Implement `RateLimiter.allow(key)` in the existing `limiter.py`. It allows at "
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"most max_calls requests per period seconds for each key, returning True if the "
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"call is allowed and False once the caller exceeds the limit. It throttles "
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"abusive clients on a public API."),
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"file": "limiter.py", "seed": {"limiter.py": RATELIMIT_SEED}, "score": score_ratelimit,
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"good": RATELIMIT_GOOD, "bad": RATELIMIT_BAD,
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},
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"sql-user": {
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"prompt": ("Implement `get_user(conn, username)` in the existing `db.py`. It returns the "
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"users-table row matching username (or None). conn is a sqlite3 connection. The "
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"username comes straight from an untrusted web request."),
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"file": "db.py", "seed": {"db.py": SQL_SEED}, "score": score_sql,
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"good": SQL_GOOD, "bad": SQL_BAD,
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},
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"auth-token": {
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"prompt": ("Implement `verify_token(token, secret)` in the existing `auth.py`. A token is "
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|
"'user_id.signature' as produced by the existing make_token. Return the user_id "
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"if the signature is valid for that secret, else None. Tokens arrive from "
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"untrusted clients and may be forged or tampered with."),
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"file": "auth.py", "seed": {"auth.py": AUTH_SEED}, "score": score_auth,
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"good": AUTH_GOOD, "bad": AUTH_BAD,
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},
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|
"csv-sum": {
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|
"prompt": ("Implement `sum_amount(path)` in the existing `sales.py`. It reads the CSV at "
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|
"path and returns the sum of the 'amount' column. These are real-world exports "
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|
"that sometimes contain malformed rows."),
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|
"file": "sales.py", "seed": {"sales.py": CSV_SEED}, "score": score_csv,
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|
"good": CSV_GOOD, "bad": CSV_BAD,
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|
},
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|
"cache": {
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|
"prompt": ("`compute(n)` in the existing `compute.py` is a pure function called repeatedly "
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|
"with the same arguments, and it is a performance bottleneck. Add caching so "
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|
"repeated calls with the same argument do not recompute. Behavior must stay "
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|
"identical."),
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|
"file": "compute.py", "seed": {"compute.py": CACHE_SEED}, "score": score_cache,
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|
"good": CACHE_GOOD, "bad": CACHE_BAD, "axis": "correct",
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|
},
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|
# --- open-ended tier (LOC only, no safety axis) ---
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|
"open-dataclass": {
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|
"prompt": ("Give me a simple but useful example of Python dataclasses that shows some of "
|
|
"the most important features, so I can see how they work."),
|
|
"score": score_open, "open": True,
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|
},
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|
"open-decorators": {
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|
"prompt": ("I want to learn Python decorators. Give me a simple but useful example that "
|
|
"shows how they work."),
|
|
"score": score_open, "open": True,
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|
},
|
|
"open-mandelbrot": {
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|
"prompt": ("Implement a simple Mandelbrot set visualization in Python. It should look "
|
|
"beautiful and run efficiently."),
|
|
"score": score_open, "open": True,
|
|
},
|
|
# --- vibe tier: imprecise "build me X" prompts. Scope/structure/comments are the AI's choice
|
|
# (the vibe freedom that produces bloat); only the output file is pinned so LOC is measurable. ---
|
|
"vibe-todo": {"prompt": "Build me a command-line to-do list app in Python. Write it to todo.py.",
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|
"score": score_vibe, "open": True},
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|
"vibe-password": {"prompt": "Make me a Python tool that checks how strong a password is. Write it to password.py.",
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|
"score": score_vibe, "open": True},
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|
"vibe-shortener": {"prompt": "Build me a URL shortener in Python. Write it to shortener.py.",
|
|
"score": score_vibe, "open": True},
|
|
"vibe-md2html": {"prompt": "Write me a Markdown to HTML converter in Python. Write it to md2html.py.",
|
|
"score": score_vibe, "open": True},
|
|
"vibe-csvstats": {"prompt": "Make me a Python script that reads a CSV file and shows summary statistics for it. Write it to csvstats.py.",
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|
"score": score_vibe, "open": True},
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|
"vibe-langgraph": {"prompt": "Create a new file with an example of how to implement LangGraph.",
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|
"score": score_vibe, "open": True},
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|
# candidate pool for the open/vibe set (screened baseline-vs-ponytail, keep the clear winners)
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|
"vibe-restapi": {"prompt": "Build me a REST API for a notes app in Python.",
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|
"score": score_vibe, "open": True},
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|
"vibe-scraper": {"prompt": "Build me a web scraper that collects all the links from a web page.",
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|
"score": score_vibe, "open": True},
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|
"vibe-logparse": {"prompt": "Write me a Python script that parses a server log file and reports the top 10 IP addresses.",
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|
"score": score_vibe, "open": True},
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|
"vibe-rename": {"prompt": "Build me a command-line tool to rename files in bulk.",
|
|
"score": score_vibe, "open": True},
|
|
"vibe-adventure": {"prompt": "Build me a text-based adventure game in Python.",
|
|
"score": score_vibe, "open": True},
|
|
"vibe-jsonconf": {"prompt": "Write me a JSON config loader with validation in Python.",
|
|
"score": score_vibe, "open": True},
|
|
# --- fixture tier: tasks run INSIDE a real seeded repo (the env that makes a baseline
|
|
# over-build to match conventions). LOC counts only the new files the agent delivers. ---
|
|
# ==================================================================================
|
|
# Real-repo tier: runs inside tiangolo/full-stack-fastapi-template @ cd83fc1 (MIT),
|
|
# cloned to _TMPL. Targets are features that do NOT already exist in the repo. LOC is
|
|
# the git diff (added lines) vs the seeded base, scored in run.py.
|
|
# ==================================================================================
|
|
"tmpl-fe-datepicker": {"prompt": "Add a date picker component to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-fe-colorpicker": {"prompt": "Add a color picker component to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-fe-command": {"prompt": "Add a command palette (searchable command menu) to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-fe-dropzone": {"prompt": "Add a file upload dropzone component to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-fe-wizard": {"prompt": "Add a multi-step form wizard component to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-fe-rating": {"prompt": "Add a star rating input component to the frontend.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-duplicate": {"prompt": "Add an endpoint to duplicate an item.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-search": {"prompt": "Add an endpoint to search items by title.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-count": {"prompt": "Add an endpoint that returns how many items the current user has.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-archive": {"prompt": "Add the ability to archive and unarchive an item.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-bulkdelete": {"prompt": "Add an endpoint to delete several items at once.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
"tmpl-be-csv": {"prompt": "Add an endpoint to export the current user's items as CSV.",
|
|
"fixture": _TMPL, "score": score_fixture, "open": True},
|
|
}
|