Transforms legacy repositories into AI-agent-ready codebases. Exposes transform, score, evaluate, and review_pr as MCP tools for Claude Code, VS Code, and MCP-compatible clients.
Four tools with complete schemas and descriptions, but significant gaps in parameter documentation and error handling guidance. Tool names are action-oriented (transform, score, evaluate, review_pr) and descriptions are substantive (100-200 chars). However, many parameters lack descriptions or constraints. The 'transform' tool has good parameter coverage, but 'evaluate' and 'review_pr' have minimal parameter documentation. No error recovery guidance visible. Output schemas are not formally documented. Composition is reasonable, tools are single-purpose, but chaining support is unclear.
Run the AgentReady evaluation framework: generates 15 repo-specific questions, asks them with and without context files, and judges responses using a three-specialist panel (Factual Accuracy, Semantic Equivalence, Operational Safety). Returns per-question verdicts, scores, and a summary verdict. Takes 2–3 minutes — requires scaffolding files to already exist.
Review a GitHub pull request grounded in agent-context.json. Posts an APPROVE or REQUEST_CHANGES review with file-specific comments. The review understands your architecture, restricted paths, domain concepts, and known pitfalls before reading a single line of diff.
Return the 100-point agentic readiness score for a repository. Checks for all scaffolding files locally — no LLM call, instant result.
Transform a repository into an AI-agent-ready codebase. Runs the full pipeline: collect → analyse → generate scaffolding files (AGENTS.md, CLAUDE.md, system_prompt.md, agent-context.json, mcp.json, memory/schema.md). Returns the agentic readiness score when done.
Parameter descriptions missing or minimal for 'evaluate' and 'review_pr'. The 'fail_level' parameter in 'evaluate' lacks guidance on interpretation (0.0 - 1.0 range stated but no explanation of what constitutes pass/fail). 'review_pr' parameters lack detail on expected behavior and error conditions.
No output schema documentation. Tools return strings or structured results, but the exact fields, types, and structure are not formally documented. LLMs cannot plan downstream calls or extract specific fields without seeing the response schema.
No error recovery guidance. Tools can fail (e.g., missing API key, invalid path, GitHub auth failure) but descriptions do not explain what to do next. LLMs receive raw errors with no actionable recovery path.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 63 | 2026-07-28+ | v2 |
Parameter constraints not fully specified. 'provider' accepts multiple values but no enum constraint visible in schema. 'only' parameter in 'transform' lists valid values in description ('agents, tools, context, or memory') but should be an enum. Free-form strings invite hallucinated values.
Destructive operations lack confirmation pattern. 'transform' with force=true overwrites files; 'review_pr' posts to GitHub. No dry-run confirmation or explicit warning that these are irreversible. Agents may accidentally destroy work.