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Vovk.ts OpenAPI mixins — importing third-party OpenAPI 3.x schemas as typed client modules that share the same call signature as native Vovk RPC modules. Use whenever the user asks to "call a third-party API from my Vovk app", "mixin an OpenAPI schema", "import an OpenAPI spec as a client", "wrap an external service that only ships an OpenAPI doc", or mentions `openAPIMixin`, `getModuleName`, `getMethodName`, `withDefaults` on a generated API module, or the `Mixins` namespace. Also use to push back when the user reaches for mixins for a vendor with a great official SDK (Stripe, AWS, GitHub via Octokit) — the skill explains when the official client is the better choice. Covers remote/local/inline specs, module + method naming strategies, `apiRoot`, per-mixin fetcher, AJV client validation knobs, and composed/segmented clients. **`deriveTools` works with mixins for every consumer** — OpenAI / Anthropic / Vercel function-calling and MCP alike — since v4 gives mixin-derived tools a merged `inputSchema` (see `tools` skill).

The skillemall take

The skill teaches how to import OpenAPI schemas as typed modules into Vovk.ts applications. Promises the same call interface for external APIs and native RPC modules via `openAPIMixin`, `getModuleName`, `getMethodName`, `withDefaults`.

One file, 3667 tokens, no critical errors. Quality score of 61 signals incompleteness: description is truncated (lint error), no model runs recorded. Covers local and remote schemas, but specifics on type setup and error handling are missing from the data. Advises against mixins when official SDKs exist (Stripe, AWS, Octokit)—sensible guidance.

Install if you're integrating APIs into Vovk.ts that ship OpenAPI specs only. Without a full working example and complete function docs, proceed at your own risk.

finom/vovk Agent Skills author: finom 1 file body ≈ 3 667 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Vovk.ts OpenAPI mixins — importing third-party OpenAPI 3.x schemas as typed client modules that share the same call signature as native Vovk RPC modules. Use…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationGitHubStripeAWSAI 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
C
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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

  • error description-long description is 1034 chars, limit 1024
  • note edit-residue the text marks something as outdated (lines 10, 18): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 57/100

  • 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
  • 30Running it twice. 12 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 18 steps, 2 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3667 tokens
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1034: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.