mirror of
https://github.com/affaan-m/everything-claude-code.git
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a2e465c74d
* feat(skills): add skill-comply — automated behavioral compliance measurement Automated compliance measurement for skills, rules, and agent definitions. Generates behavioral specs, runs scenarios at 3 strictness levels, classifies tool calls via LLM, and produces self-contained reports. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(skill-comply): address bot review feedback - AGENTS.md: fix stale skill count (115 → 117) in project structure - run.py: replace remaining print() with logger, add zero-division guard, create parent dirs for --output path - runner.py: add returncode check for claude subprocess, clarify relative_to path traversal validation - parser.py: use is_file() instead of exists(), catch KeyError for missing trace fields, add file check in parse_spec - classifier.py: log warnings on malformed classification output, guard against non-dict JSON responses - grader.py: filter negative indices from LLM classification Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
73 lines
2.2 KiB
Python
73 lines
2.2 KiB
Python
"""Generate compliance specs from skill files using LLM."""
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from __future__ import annotations
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import subprocess
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import tempfile
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from pathlib import Path
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import yaml
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from scripts.parser import ComplianceSpec, parse_spec
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from scripts.utils import extract_yaml
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PROMPTS_DIR = Path(__file__).parent.parent / "prompts"
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def generate_spec(
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skill_path: Path,
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model: str = "haiku",
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max_retries: int = 2,
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) -> ComplianceSpec:
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"""Generate a compliance spec from a skill/rule file.
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Calls claude -p with the spec_generator prompt, parses YAML output.
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Retries on YAML parse errors with error feedback.
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"""
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skill_content = skill_path.read_text()
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prompt_template = (PROMPTS_DIR / "spec_generator.md").read_text()
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base_prompt = prompt_template.replace("{skill_content}", skill_content)
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last_error: Exception | None = None
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for attempt in range(max_retries + 1):
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prompt = base_prompt
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if attempt > 0 and last_error is not None:
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prompt += (
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f"\n\nPREVIOUS ATTEMPT FAILED with YAML parse error:\n"
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f"{last_error}\n\n"
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f"Please fix the YAML. Remember to quote all string values "
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f"that contain colons, e.g.: description: \"Use type: description format\""
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)
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result = subprocess.run(
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["claude", "-p", prompt, "--model", model, "--output-format", "text"],
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capture_output=True,
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text=True,
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timeout=120,
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)
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if result.returncode != 0:
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raise RuntimeError(f"claude -p failed: {result.stderr}")
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raw_yaml = extract_yaml(result.stdout)
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tmp_path = None
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".yaml", delete=False,
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) as f:
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f.write(raw_yaml)
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tmp_path = Path(f.name)
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try:
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return parse_spec(tmp_path)
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except (yaml.YAMLError, KeyError, TypeError) as e:
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last_error = e
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if attempt == max_retries:
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raise
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finally:
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if tmp_path is not None:
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tmp_path.unlink(missing_ok=True)
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raise RuntimeError("unreachable")
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