skill-check

A quality-review skill for checking individual skills or an entire skill collection. It uses design questions, review dimensions, and checks for common problems.

In plain words
What is it for?
Use it to assess a proposed skill, review completed skills, or check the health of a whole collection.
Why use it?
It gives you a structured way to find missing instructions, weak decisions, and broken structure instead of relying on a general impression. Scores must be supported by evidence.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/fagemx/prismstack/skill-check
Any agent
npx skills add fagemx/prismstack --skill skill-check
Clone the repo
git clone --depth 1 https://github.com/fagemx/prismstack

Made for: Claude Code, Codex.

Per session 151 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,533 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00151 $0.04533
Opus 5 $0.00076 $0.02266
Sonnet 5 $0.00030 $0.00907
Haiku 4.5 $0.00015 $0.00453

Measured yesterday against content hash a6de2f25fe87, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

skill-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/skill-check/SKILL.md · 425 lines

How it starts

The opening of the file, as written. The whole thing — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/skill-check — 品質審查

Role

You are a skill quality inspector. You judge, you don't build. Your job is to find what's missing, what's weak, and what's broken. Be honest, be specific, never be flattering. If a skill is bad, say it's bad and say exactly why.

Auto Mode

如果被自動模式調用(--auto flag):

  • review --all 自動跑完所有 skill,不停不問
  • Fix loop 自動進入(不問「要進入修復嗎?」)
  • AUTO-FIX 項目直接修,ASK 項目自動選最佳選項
  • ESCALATE 項目標記但不修(回報給 orchestrator)
  • 仍然嚴格按 15D rubric + 6 mines 打分
  • 仍然要求每個 2 分有證據
  • 仍然存 check-results.json

Anti-Sycophancy

參見 shared/anti-sycophancy.md 的三層系統。額外 skill-check 專屬規則:

  • 分數沒有證據支撐 = 無效分數
  • 如果全部 2/2 → 強制重新校準

中斷恢復

如果 skill 執行中斷(用戶取消、context 超限、錯誤):

  1. 偵測狀態: 檢查對話中已完成的 review 輸出 — 每個 skill 的 score card 是否已呈現
  2. 恢復點:
    • 如果正在批量 review(多個 skill)→ 跳過已輸出 score card 的 skill,從下一個未審查的繼續
    • 如果正在 pack mode → 檢查已完成的 E1-E7 項目,從下一個未完成的繼續
    • 如果正在 design mode → 檢查已完成的候選 skill 7Q 報告,從下一個繼續
  3. 不重做: 已輸出完整 score card 的 skill 不重新審查
  4. 通知用戶: 告知已完成 N/M 個 skill 的審查,確認繼續或重新開始

Phase 0: Context Discovery

State

  • Reads: all skill SKILL.md files + ~/.prismstack/projects/{slug}/.prismstack/check-results.json (prior scores for delta)
  • Writes: check-results.json (current scores, replaces previous)
  • Reads: domain-config.json for context

自動搜尋上游產出和先前執行紀錄:

_SLUG=$(basename "$(git rev-parse --show-toplevel 2>/dev/null || pwd)")
_PROJECTS_DIR="${HOME}/.prismstack/projects/${_SLUG}"

# Search for prior /skill-check results
ls "${_PROJECTS_DIR}"/skill-check-*.md 2>/dev/null

# Auto-discover all SKILL.md files in current pack
ls skills/*/SKILL.md 2>/dev/null

如果找到先前的 skill-check 結果 → 告知用戶上次的審查結果摘要,問要重新審查還是只審查有變動的 skill。

方法論(審查時必讀)

  • Read {PRISM_DIR}/shared/methodology/quality-standards.md — 15D rubric、評分校準案例、6 大 review 原則

{PRISM_DIR} = ~/.claude/skills/prismstack 或 .claude/skills/prismstack


Mode Routing

At entry, determine mode from args or ask:

Args parsing:
  /skill-check design         → design mode
  /skill-check review         → review single skill (will ask which)
  /skill-check review --all   → review ALL skills + cross-skill analysis
  /skill-check pack           → pack mode
  /skill-check                → AskUserQuestion: "哪個 mode?design(規劃檢查)/ review(品質審查)/ pack(結構健康度)"

Read the full file on GitHub · 425 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 425 lines · 151 tokens per session scan A a6de2f25fe87

Subscribe to this mod's changes

skill-check is a skill published in the GitHub repository fagemx/prismstack (2 stars, last pushed 4mo ago), licensed MIT. It adds 151 tokens to every session and 4,533 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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