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技能熔炉 — 锻造/评估/改进 Skill。说 技能熔炉 走全流程（含R5改进已有skill）；说 技能评估/skill评估/评估技能 只做同类比对+腾讯9维度。可选能力：搜索SkillHub同类技能（通过TRAE内置工具）、修改已有skill文件（仅R5诊断修复路径，需用户确认）。发布环节请用 skill-publisher。Do NOT use for skill security vetting, skill publishing (use skill-publisher), or general coding tasks.

ClawHub Agent Skills author: AI花生 v6.4.0 MIT-0 16 files body ≈ 1 712 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

技能熔炉 — 锻造/评估/改进 Skill。说 技能熔炉 走全流程（含R5改进已有skill）；说 技能评估/skill评估/评估技能 只做同类比对+腾讯9维度。可选能力：搜索SkillHub同类技能（通过TRAE内置工具）、修改已有skill文件（仅R5诊断修复路径，需用户确认）。发布环节请用…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "displayName"
    • note frontmatter-key unknown frontmatter key "summary"

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 40Consistency. Frontmatter name (skill-forge) differs from the folder (skill-forge-ai)
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 16 steps
    • 100Execution cost. Instruction body is 1712 tokens
    • low 11 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 268: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This is a disclosed skill-building assistant that can create or edit skill files with user confirmation and shows no hidden credential access, persistence, publishing, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 20 Jul 2026