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BD get-api-docs

Use this skill to get documentation for third-party APIs, SDKs or libraries before writing code that uses them to ensure you have the latest, most accurate documentation. This is a better way to find documentation than doing web search. This includes when a user asks for tasks like "use the OpenAI API", "call the Stripe API", "use the Anthropic SDK", "query Pinecone", or any other time the user asks you to write code against an external service and you need current API reference. Fetch the docs with chub before answering, rather than relying on your pre-trained knowledge, which may be outdated because of recent changes to these APIs. Be sure to use this skill when the user asks for the latest docs, latest API behavior, or explicitly mentions chub or Context Hub. Ensure `chub` is available, run `chub --help`, then follow the instructions there.

mxyhi/ok-skills Agent Skills author: mxyhi Apache-2.0 1 file body ≈ 545 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Use this skill to get documentation for third-party APIs, SDKs or libraries before writing code that uses them to ensure you have the latest, most accurate…

As a process D 43/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

IntegrationStripeWriting and documentsSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
D
43/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

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: 1. 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 43/100

    • 0Steps. Prose only: no discrete steps
    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 545 tokens
    • 100Running it twice. No mutating operations

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 856: 120–800 characters recommended
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +4Structure: 5 headings
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.