AgentStack
SKILL verified MIT Self-run

Ywc Codex Toolkit Eval

skill-yongwoon-ywc-agent-toolkit-ywc-codex-toolkit-eval · by yongwoon

>-

No reviews yet
0 installs
23 views
0.0% view→install

Install

$ agentstack add skill-yongwoon-ywc-agent-toolkit-ywc-codex-toolkit-eval

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

Are you the author of Ywc Codex Toolkit Eval? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

ywc-codex-toolkit-eval

Announce at start: "I'm using the ywc-codex-toolkit-eval skill to evaluate this repository's Codex skills and agents."

This local Codex skill runs a Codex-only evaluate -> improve cycle over codex/skills/* and codex/agents/*.toml. It must stay under .codex/skills/ and must not be copied into codex/skills/ or .codex-plugin/skills/.

Boundary

| Included | Excluded | |---|---| | codex/skills/*/SKILL.md | .claude/skills/* | | codex/skills/*/agents/openai.yaml | claude-code/skills/* | | codex/agents/*.toml | claude-code/agents/* | | Codex install flow, plugin packaging, and bundle docs | Application source code review |

Rationalization Defense

When tempted to bypass a rule, check this table first:

| Excuse | Reality | |---|---| | "scripts/validate.sh is green, so the Codex bundle is healthy" | Validation proves structure and packaging only. Trigger precision, workflow actionability, runtime fit, and behavioral evidence still need graded evaluation. | | "The Claude evaluator already scores Codex paths, so keep using it" | Claude Code and Codex have different frontmatter schemas, agent formats, install paths, and runtime assumptions. Shared concepts are acceptable; shared target roots are not. | | "Local evaluator skills can live under codex/skills if we remember not to publish them" | codex/skills and .codex-plugin/skills are distribution surfaces. Evaluators there will leak into installs or plugin packaging. | | "Mechanical score is enough" | Mechanical axes are partial evidence. Judgment axes such as trigger precision, workflow actionability, scope discipline, mission boundaries, and behavioral evidence still decide the grade. | | "No eval fixtures means no score" | Score from available evidence and mark uncertainty. Missing fixtures are themselves a quality signal. | | "Fix every issue while evaluating" | Evaluation produces an evidence-ranked backlog. Implement fixes through ywc-skill-author, Codex agent authoring, or bundle docs work, then re-score. | | "CI should rewrite history automatically" | CI compares against the reviewed baseline only. Baseline updates are explicit maintenance actions after reviewing the markdown scorecard. |

Violating the letter of these rules is violating the spirit. A quality cycle is useful only when it separates measurement, ownership, and repair.

Arguments

| Parameter | Format | Example | Description | |-----------|--------|---------|-------------| | --target | --target | --target codex/skills | Mechanical scorer target: codex/skills, codex/agents, or all (default). | | --item | --item | --item ywc-plan | Score one Codex skill or agent instead of the whole root. | | --mode | --mode | --mode mechanical | Skill-level evaluation mode: mechanical, judge, or full. Direct score.py runs support mechanical only; judge and full are skill-mediated workflows. | | --ci | flag | --ci | Compare deterministic axes against evals/history.mechanical.json without rewriting it. | | --update-baseline | flag | --update-baseline | Write the reviewed current mechanical baseline after checking the markdown output. | | --only | --only | --only agents | Inventory gate scope: skills, agents, or all. |

Argument Mapping

Map user arguments to concrete commands before running the workflow:

| User request | Inventory command | Mechanical command | |---|---|---| | --target all or no target | inventory_gate.py --json | score.py --mode mechanical --target all --format markdown | | --target codex/skills | inventory_gate.py --json --only skills | score.py --mode mechanical --target codex/skills --format markdown | | --target codex/agents | inventory_gate.py --json --only agents | score.py --mode mechanical --target codex/agents --format markdown | | --item | run the matching inventory scope for context | add --item to score.py and score only that asset in the judgment pass | | --ci | optional unless a full report is requested | score.py --ci | | --update-baseline | optional unless reviewing current structure | score.py --update-baseline after reviewing markdown output |

Direct score.py runs support mechanical mode only. For --mode judge or --mode full, use the mechanical output plus the rubric references to complete the judgment pass.

Scoring Model

Use three layers:

  1. Gate: run scripts/inventory_gate.py to collect inventory and structural pass/fail evidence. Gate failures cap the affected asset at grade C.
  2. Mechanical: run scripts/score.py for deterministic axes and baseline comparison. Judgment axes stay · and final_total remains unavailable.
  3. Judgment: score the remaining axes with the rubric references.

Each dimension is scored 0-4. Weighted composite maps to: A >= 3.5, B 2.5-3.49, C 1.5-2.49, `D

Verdict

  • Status: PASS | PASSWITHACTIONS | REVIEW_REQUIRED | FAIL
  • Assets evaluated:
  • Gate failures:
  • Lowest grade:

Scorecards

| Asset | Kind | Grade | Composite | Weakest dimension | Evidence | |---|---|---:|---:|---|---|

Priority Backlog

  1. [Critical|High|Medium|Low] -

Evidence: Recommended owner:

Scoreboard Update

  • Added:
  • Improved:
  • Regressed:
  • Next review scope:

## Validation

Before claiming the evaluation is complete, verify:

- [ ] `inventory_gate.py` was run for the stated scope.
- [ ] `score.py --mode mechanical --format markdown` was run for mechanical evidence unless skill-level `--mode judge` was explicit.
- [ ] Expected negative checks were run as assertion-shaped commands:
  - `! test -e codex/skills/ywc-codex-toolkit-eval`
  - `! test -e .codex-plugin/skills/ywc-codex-toolkit-eval`
  - `! rg 'tools/codex-internal/skills/ywc-codex-toolkit-[e]val' .codex/skills/ywc-codex-toolkit-eval scripts/validate.sh`
- [ ] Every scored skill used [references/skill-rubric.md](references/skill-rubric.md).
- [ ] Every scored agent used [references/agent-rubric.md](references/agent-rubric.md).
- [ ] Mechanical-only mode is reported as partial, not final quality.
- [ ] Report artifacts, if written, are under `docs/skill-agent-eval/codex/`.
- [ ] No Claude-only paths were scored as Codex assets.
- [ ] `ywc-codex-toolkit-eval` does not appear under `codex/skills/` or `.codex-plugin/skills/`.

## Common Mistakes

- **Evaluating Claude Code artifacts with this skill** — use `.claude/skills/ywc-toolkit-eval` for Claude Code.
- **Treating mechanical points as a final grade** — judgment axes must be scored before claiming a composite grade.
- **Letting local evaluator files leak into packaging** — keep the skill under `.codex/skills/`.
- **Skipping the backlog** — the prioritized fix list is the deliverable that makes the cycle actionable.

## Integration

- **Upstream**: `ywc-skill-author` for Codex skill rule interpretation.
- **Downstream**: use the prioritized backlog to make targeted Codex skill/agent edits, then re-run this skill.
- **Pairs with**: `scripts/validate.sh`, which enforces the local-only packaging boundary and runs the mechanical regression gate.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [yongwoon](https://github.com/yongwoon)
- **Source:** [yongwoon/ywc-agent-toolkit](https://github.com/yongwoon/ywc-agent-toolkit)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet — be the first.

Versions

  • v0.1.0 Imported from the upstream source.