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AC craft

Read and write Craft documents via the Craft Connect API. Use when the user asks to create, read, update, or search Craft documents, manage tasks, write daily notes, organize folders, work with collections (structured databases), or format rich content. Covers all block types including toggles, callouts, tables, code, highlights, math formulas, images, cards, and styled text. NOT for general note-taking to local files or unrelated document editors. Requires: CRAFT_API_URL (Craft Connect API base URL with embedded link token, stored in TOOLS.md). Uses curl for all HTTP requests.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 3 files body ≈ 4 103 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Read and write Craft documents via the Craft Connect API.

As a process C 54/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

IntegrationSoftware developmentMedia and videotype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 6 mutating operations with no state check
    • 40Consistency. Frontmatter name (craft) differs from the folder (craft-connect)
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4103 tokens
    • 100Steps. 17 steps
    • 100When it triggers. States when to use and when not to
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    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
    • -5TODO / placeholder text left in the skill
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 584: enough signal without eating the budget
    • +4Structure: 40 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (35 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.