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https://github.com/magnus919/agent-skills.git
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Add ruff linter/formatter with pre-commit hooks, pytest-cov with 60% coverage threshold, CODEOWNERS, Dependabot for pip/GHA updates, and .env.example. Auto-fix existing ruff violations across eval_runner/ and scripts/. 10 agent-readiness criteria resolved: lint_config, formatter, pre_commit_hooks, naming_consistency, dead_code_detection, test_coverage_thresholds, test_performance_tracking, codeowners, dependency_update_automation, env_template. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
367 lines
13 KiB
Python
367 lines
13 KiB
Python
#!/usr/bin/env python3
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"""Report eval coverage across skills and enforce ratchet thresholds.
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Phase 2: informational coverage report (always passes).
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Phase 3: ratchet — warn at 25%, fail-on-modify at 50%.
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Usage:
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python3 scripts/eval-coverage.py # human-readable report
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python3 scripts/eval-coverage.py --json # machine-readable
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python3 scripts/eval-coverage.py --modified-from REF # ratchet check
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"""
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import argparse
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import io
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import json
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import subprocess
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import sys
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import tarfile
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import tempfile
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from pathlib import Path
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from eval_validation import NOT_ASSESSED, STATE_NAMES, ValidationResult, validate_manifest
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ROOT = Path(__file__).resolve().parent.parent
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# Phase 3 ratchet thresholds (percent of skills with evals)
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WARN_THRESHOLD = 25 # modified skills without evals get a warning
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FAIL_THRESHOLD = 50 # modified skills without evals fail CI
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# Pathspec that matches every tracked file under a canonical skill directory.
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# A canonical skill lives at <root>/<skill-name>/SKILL.md or
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# <root>/bundles/<bundle-name>/skills/<skill-name>/SKILL.md. The glob
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# ``*/SKILL.md`` covers the first shape; ``bundles/*/skills/*/SKILL.md``
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# covers the second. We use the same glob for both ls-files and diff so
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# that modified-skill detection sees the same universe as find_skills().
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SKILL_PATHSPEC = ":(glob)**/SKILL.md"
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def find_skills() -> list[Path]:
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"""Find all canonical skill directories via git-tracked SKILL.md files."""
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result = subprocess.run(
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["git", "ls-files", "-z", "--", SKILL_PATHSPEC],
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cwd=ROOT,
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check=True,
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capture_output=True,
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)
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skills = []
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for name in result.stdout.decode().split("\0"):
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if not name or "/agent-council/profiles/skills/" in name:
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continue
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skills.append(Path(name).parent)
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return sorted(skills)
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def resolve_ref_to_commit(ref: str) -> str:
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"""Resolve *ref* to a commit SHA or raise ValueError.
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The caller must use only the returned SHA in subsequent git commands.
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"""
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result = subprocess.run(
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["git", "rev-parse", "--verify", "--end-of-options", f"{ref}^{{commit}}"],
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cwd=ROOT,
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capture_output=True,
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text=True,
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)
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if result.returncode != 0:
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raise ValueError(f"invalid --modified-from ref: {ref!r} is not an existing commit")
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return result.stdout.strip()
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def find_skills_at(ref: str) -> list[Path]:
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"""Find canonical skill directories tracked at a git revision."""
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result = subprocess.run(
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["git", "ls-tree", "-r", "--name-only", ref, "--"],
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cwd=ROOT,
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check=True,
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capture_output=True,
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text=True,
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)
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skills = []
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for name in result.stdout.splitlines():
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if name.endswith("/SKILL.md") and "/agent-council/profiles/skills/" not in name:
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skills.append(Path(name).parent)
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return sorted(skills)
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def check_eval_states(skill_dir: Path) -> ValidationResult:
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"""Return validation and evidence states for one skill."""
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evals_file = ROOT / skill_dir / "evals" / "evals.json"
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return validate_manifest(evals_file, ROOT)
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def check_evals(skill_dir: Path) -> tuple[bool, int]:
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"""Return (has_schema_valid_manifest, case_count) for compatibility."""
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result = check_eval_states(skill_dir)
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return result.states["schema_valid"] is True, result.case_count
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def count_references(skill_name: str, all_skill_dirs: list[Path]) -> int:
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"""Count how many other SKILL.md files mention this skill name."""
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count = 0
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for skill_dir in all_skill_dirs:
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skill_md = ROOT / skill_dir / "SKILL.md"
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if not skill_md.exists():
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continue
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try:
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if skill_name in skill_md.read_text(encoding="utf-8"):
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count += 1
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except OSError:
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pass
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return count
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def modified_skills(base_ref_commit: str) -> set[Path]:
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"""Return skill directories with any tracked file changed since base_ref.
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A skill is considered modified when *any* file under its directory
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changes — not just SKILL.md. This covers references, scripts,
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fixtures, README, and eval manifests.
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"""
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result = subprocess.run(
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["git", "diff", "--name-only", base_ref_commit, "HEAD", "--"],
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cwd=ROOT,
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capture_output=True,
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text=True,
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)
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changed_files = [
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line
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for line in result.stdout.strip().splitlines()
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if line and "/agent-council/profiles/skills/" not in line
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]
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# Map each changed file to its owning skill directory by checking
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# whether the file path starts with a known skill directory prefix.
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# Include skills from both revisions so complete directory deletions
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# remain observable under their old name.
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known_skills = sorted(
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set(find_skills()) | set(find_skills_at(base_ref_commit)),
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key=lambda path: len(path.parts),
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reverse=True,
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)
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modified: set[Path] = set()
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for changed in changed_files:
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changed_path = Path(changed)
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for skill_dir in known_skills:
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try:
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changed_path.relative_to(skill_dir)
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modified.add(skill_dir)
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break
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except ValueError:
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continue
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return modified
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def evaluate_ratchet(
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modified: set[Path],
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current: set[Path],
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without_evals: set[Path],
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coverage_pct: float,
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) -> tuple[list[str], list[str]]:
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"""Apply warning and failure thresholds to modified current skills."""
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warnings: list[str] = []
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errors: list[str] = []
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for skill_dir in sorted(modified & current & without_evals):
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name = str(skill_dir)
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if coverage_pct >= FAIL_THRESHOLD:
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errors.append(
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f"{name}: modified skill has no schema-valid eval manifest "
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f"(coverage {coverage_pct:.1f}% >= {FAIL_THRESHOLD}% — "
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"evals required on modification)"
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)
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elif coverage_pct >= WARN_THRESHOLD:
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warnings.append(
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f"{name}: modified skill has no schema-valid eval manifest "
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f"(coverage {coverage_pct:.1f}% >= {WARN_THRESHOLD}% — "
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"evals recommended)"
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)
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return warnings, errors
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def coverage_decreased(base_ref_commit: str) -> tuple[bool, float, float]:
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"""Compare schema-valid eval coverage for skills retained across revisions.
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Removed skills do not count as a regression; retained skills losing a
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valid manifest do. New skills are governed by the modified-skill ratchet.
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"""
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head_skills = find_skills()
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# Compare only skills present at both revisions. Removing a skill should
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# not count as a coverage regression, while removing or invalidating the
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# eval manifest of a retained skill still must fail the ratchet.
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base_skill_dirs = set(find_skills_at(base_ref_commit))
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retained_skill_dirs = base_skill_dirs & set(head_skills)
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base_with = 0
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archive = subprocess.run(
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["git", "archive", "--format=tar", base_ref_commit, "--"],
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cwd=ROOT,
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check=True,
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capture_output=True,
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).stdout
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with tempfile.TemporaryDirectory() as tmp:
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snapshot = Path(tmp)
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with tarfile.open(fileobj=io.BytesIO(archive), mode="r:") as tar:
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tar.extractall(snapshot, filter="data")
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subprocess.run(["git", "init", "-q"], cwd=snapshot, check=True)
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subprocess.run(
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["git", "add", "-f", "--all"],
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cwd=snapshot,
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check=True,
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capture_output=True,
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)
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for skill_dir in retained_skill_dirs:
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manifest = snapshot / skill_dir / "evals" / "evals.json"
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if validate_manifest(manifest, snapshot).states["schema_valid"] is True:
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base_with += 1
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# Use the same retained-skill population on both sides of the comparison.
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# New and deleted skills are handled by their own ratchet rules.
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head_with_retained = sum(
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1 for skill_dir in retained_skill_dirs if check_evals(skill_dir)[0]
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)
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base_pct = (
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base_with / len(retained_skill_dirs) * 100 if retained_skill_dirs else 0.0
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)
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head_pct = (
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head_with_retained / len(retained_skill_dirs) * 100
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if retained_skill_dirs
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else 0.0
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)
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return head_pct < base_pct, base_pct, head_pct
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def main() -> int:
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parser = argparse.ArgumentParser(description="Eval coverage report and ratchet")
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parser.add_argument("--json", action="store_true", help="JSON output")
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parser.add_argument(
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"--modified-from",
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metavar="REF",
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help="Apply ratchet only to skills modified since REF",
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)
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args = parser.parse_args()
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resolved_base_ref = None
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if args.modified_from:
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try:
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resolved_base_ref = resolve_ref_to_commit(args.modified_from)
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except ValueError as exc:
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print(f"ERROR: {exc}", file=sys.stderr)
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return 2
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skills = find_skills()
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total = len(skills)
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skill_states: list[dict] = []
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without_evals: list[str] = []
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for skill_dir in skills:
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validation = check_eval_states(skill_dir)
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has = validation.states["schema_valid"]
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count = validation.case_count
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name = str(skill_dir)
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skill_states.append({"skill": name, "cases": count, **validation.states})
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if has is not True:
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without_evals.append(name)
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supported_states = ("manifest_present", "schema_valid")
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state_summary: dict[str, dict[str, object]] = {}
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for state in supported_states:
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count = sum(1 for entry in skill_states if entry[state] is True)
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state_summary[state] = {
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"assessment": "supported",
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"count": count,
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"percentage": round((count / total * 100) if total else 0.0, 1),
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}
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not_assessed_reasons = {
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"executable_grader_bindings_present": "No repository contract for executable grader bindings in schema v1.",
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"recent_run_evidence_present": "No versioned provenance/freshness contract is defined for schema v1.",
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"release_gated_evidence_present": "No versioned release-gate contract is defined for schema v1.",
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}
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for state in STATE_NAMES:
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if state in state_summary:
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continue
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state_summary[state] = {
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"assessment": NOT_ASSESSED,
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"count": None,
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"percentage": None,
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"reason": not_assessed_reasons[state],
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}
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coverage_pct = state_summary["schema_valid"]["percentage"]
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# Sort skills without evals: most-referenced first, then alphabetical
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ref_counts = {name: count_references(Path(name).name, skills) for name in without_evals}
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without_evals.sort(key=lambda n: (-ref_counts[n], n))
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# Phase 3 ratchet check
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ratchet_warnings: list[str] = []
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ratchet_errors: list[str] = []
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if resolved_base_ref:
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modified = modified_skills(resolved_base_ref)
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ratchet_warnings, ratchet_errors = evaluate_ratchet(
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modified=modified,
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current=set(skills),
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without_evals={Path(name) for name in without_evals},
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coverage_pct=coverage_pct,
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)
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# Monotonic coverage floor: fail if coverage decreased.
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decreased, base_pct, head_pct = coverage_decreased(resolved_base_ref)
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if decreased:
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ratchet_errors.append(
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f"eval coverage decreased from {base_pct:.1f}% to {head_pct:.1f}% "
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f"(base {args.modified_from} → HEAD) — coverage must not regress"
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)
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if args.json:
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print(
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json.dumps(
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{
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"total_skills": total,
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"states": state_summary,
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"skills": skill_states,
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"ratchet": {
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"warn_threshold": WARN_THRESHOLD,
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"fail_threshold": FAIL_THRESHOLD,
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"warnings": ratchet_warnings,
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"errors": ratchet_errors,
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},
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},
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indent=2,
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)
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)
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else:
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print("Eval evidence states (a manifest alone does not prove behavioral quality):")
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for state in STATE_NAMES:
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summary = state_summary[state]
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if summary["assessment"] == "supported":
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print(
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f" {state}: {summary['count']}/{total} skills ({summary['percentage']:.1f}%)"
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)
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continue
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print(f" {state}: not assessed ({summary['reason']})")
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print()
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print(
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f"Skills WITHOUT schema-valid eval manifests ({len(without_evals)}), by reference count:"
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)
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for name in without_evals:
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refs = ref_counts.get(name, 0)
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print(f" - {name} (referenced by {refs} skills)")
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print()
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print(f"Ratchet: warn at {WARN_THRESHOLD}%, fail-on-modify at {FAIL_THRESHOLD}%")
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if ratchet_warnings:
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print()
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print("Ratchet warnings:")
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for w in ratchet_warnings:
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print(f" WARNING: {w}")
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if ratchet_errors:
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print()
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print("Ratchet errors:")
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for e in ratchet_errors:
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print(f" ERROR: {e}")
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return 1 if ratchet_errors else 0
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if __name__ == "__main__":
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sys.exit(main())
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