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maxgfr/ultraeval

Evaluate a skill or codebase with a multi-agent workflow, ground every finding in a real file:line, and generate an AI-exploitable TDD fix backlog. A skills.sh agent skill.

ultraeval とは?

ultraeval is a Claude Code agent skill that evaluate a skill or codebase with a multi-agent workflow, ground every finding in a real file:line, and generate an AI-exploitable TDD fix backlog. A skills.sh agent skill.

対応Claude Code~Codex CLI~Cursor
npx skills add maxgfr/ultraeval

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ドキュメント

ultraeval: evaluate a skill or codebase → grounded, AI-exploitable fix docs

The markdown is the program. A tiny deterministic engine scaffolds the run, generates the multi-agent workflow, and enforces a grounding gate; you (with fanned-out subagents) do the research, judgment, and writing. Every finding must resolve to a real file:line in the target — the gate rejects hallucinated ones — and the output is a prioritized backlog plus per-fix TDD cards a model can implement red→green→refactor.

When to use

  • "Evaluate / audit / grade / score this skill (or repo)"; "is it production-ready / does it meet expectations?"
  • "Review this codebase and give me a fix plan / a TDD backlog."
  • Regression-proofing your own skills after changes, or vetting a third-party one before trusting it.

Not for: a quick one-file code review (just read it); running the target's own test suite (do that directly).

The loop

init → plan → run(research → test-plan → execute+gates → judge → results) → verify → backlog(TDD) → score → render

Everything is a plain node <skill-dir>/scripts/ultraeval.mjs <cmd> call. Fanning out subagents is an optimization the generated workflow encodes — never a requirement.

Inputs to confirm

  • Target — a path to the skill/repo to evaluate (or a git URL the user has already cloned locally).
  • Kindskill or codebase (auto-detected: a SKILL.md ⇒ skill). Override with --kind.
  • Category — e.g. "agent skill", "CLI", "library", "web app", "security tool". Steers the starter rubric.
  • Modeaudit (defects, default) · improve (grounded improvement opportunities) · deep (both). Set with --mode.

Modes & improvement discovery

ultraeval finds two things, both grounded and gated:

  • Defects (audit, deep) — something is wrong; each cites a real file:line.
  • Opportunities (improve, deep) — a grounded improvement lead (internal health and product/capability), rated impact × effort. Discovered by analyze (deterministic hotspots/deps/churn/test-gaps) → brainstorm (divergent lenses) → brainstorm --rank (folds ranked opportunities into findings.json as kind:"opportunity"). The same gate applies — an opportunity must anchor to real code/metrics, so it never becomes vague "rewrite everything". See references/analysis-playbook.md.

For improve/deep, plan adds Analyze and Brainstorm stages to the generated workflow.

Procedure

1. Scaffold the run.

node <skill-dir>/scripts/ultraeval.mjs init --target <PATH> --out <RUN> [--kind skill|codebase] [--category "<c>"]

Writes eval.config.json with starter dimensions (see references/rubric-library.md).

2. Generate the workflow + subagent contracts.

node <skill-dir>/scripts/ultraeval.mjs plan --run <RUN>

Emits <RUN>/eval.workflow.mjs (a ready-to-launch multi-agent Workflow, with the absolute engine + target paths baked in), <RUN>/agents/*.md (the dispatch contracts), TEST-PLAN.template.md, dimensions.json, findings.schema.json.

3. Run the eval. Launch the generated workflow with your harness's Workflow tool: Workflow({ scriptPath: "<RUN>/eval.workflow.mjs" }). It pipelines Research → TestPlan → Execute → Findings → Gate → Judge → Results and self-invokes the engine gates. If you have no workflow harness, run the stages by hand: read each agents/<stage>.md and dispatch a subagent per the contract. See references/orchestration.md. Every subagent gets the ABSOLUTE <skill-dir>/scripts/ultraeval.mjs path — it has its own cwd and cannot resolve a relative one (plan already bakes the absolute path into the workflow).

4. Ground every finding. Consolidate results into <RUN>/findings.json (schema: references/gate-contract.md). Each finding cites evidence[].ref as path:line in the target or run:relpath#Lnn in a produced log. Then:

node <skill-dir>/scripts/ultraeval.mjs check --run <RUN>

Fix findings.json until it exits 0 — repair or delete ungrounded findings; never weaken the gate.

5. Verify (adversarial exit gate).

node <skill-dir>/scripts/ultraeval.mjs verify --run <RUN>          # writes VERIFY.todo.json
# fill each verdict: supported | partial | refuted | unsupported (use skeptic subagents; --shards N --shard i to parallelize)
node <skill-dir>/scripts/ultraeval.mjs verify --run <RUN> --apply <verdicts.json>
node <skill-dir>/scripts/ultraeval.mjs check --run <RUN> --semantic --require-verify   # exit gate — never present before this passes

A refuted finding must be set dismissed. A supported/partial one survives.

6. Remediate — the deliverable.

node <skill-dir>/scripts/ultraeval.mjs backlog --run <RUN> --tdd

Emits BACKLOG.json (a machine-readable, priority-ordered task list a downstream agent can execute), REMEDIATION.md, and one fixes/FIX-*.md TDD card per confirmed finding — each with a RED failing-test-first spec, the GREEN change, and a VERIFY command. See references/tdd-remediation.md.

7. Score + render + present.

node <skill-dir>/scripts/ultraeval.mjs score --run <RUN>           # judges.jsonl + dimensions -> scorecard.json (0-100 + meets-expectations)
node <skill-dir>/scripts/ultraeval.mjs render --run <RUN>          # index.html + index.md dashboard (shows the verdict)

score reduces the judge panel's judges.jsonl and the config dimensions to a weighted verdict; a live P0 finding (or any judge voting no, or a score below the bar) caps meets-expectations at false. Present the verdict, the P0/P1 backlog headline, and the paths (RESULTS.md, BACKLOG.json, fixes/) a fix agent should consume.

Exit codes across the CLI: 0 ok / gate passed · 1 gate failed (check/verify) · 2 usage or runtime error.

8. (optional) Drive the fixes. Hand each fixes/FIX-*.md to a build agent to implement TDD — the card is written so it can go red→green→refactor without re-deriving the problem.

The grounding contract

A finding is only trustworthy if its evidence resolves. check opens each path:line in the target and confirms the line exists and is in range; a stale/invented line is a hard failure. verify then asks a skeptic whether the cited content actually supports the claim. This two-layer gate (structural + semantic) is the whole point — full grammar and pass/fail rules in references/gate-contract.md.

Method & rubrics

  • references/eval-playbook.md — the research→test-plan→execute→judge→results method, and how to build a scored rubric per dimension.
  • references/orchestration.md — the generated workflow, the subagent dispatch contracts, and the absolute-<skill-dir> invariant for fan-out.
  • references/gate-contract.mdfindings.json schema, evidence-ref grammar, and exactly what makes check/verify pass or fail.
  • references/tdd-remediation.md — the BACKLOG.json shape and the fixes/FIX-*.md TDD-card format.
  • references/rubric-library.md — starter dimensions per target category.
  • references/analysis-playbook.md — the analyze signals, the brainstorm lenses, and how opportunities stay grounded.

Safety

  • ultraeval only reads the target and writes under <RUN>. It never executes the target's code; the executor subagent may run the target's own commands (tests, gates) — sandbox untrusted repos.
  • clean --run <RUN> removes only derived gate/render artifacts and keeps the deliverables; --all removes the whole run.

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