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CD lmstudio-api

Справочник по HTTP-API LM Studio (сервер локальных моделей, обычно порт 1234). Используй когда надо программно управлять моделями на LM Studio - узнать что загружено, загрузить или выгрузить модель, задать длину контекста и параллельность, отключить размышления модели, - а также при диагностике: модель thinking/reasoning не отключается, enable_thinking игнорируется, ответ приходит пустым а весь бюджет уходит в reasoning_content, запросы падают с HTTP 500 на холодном старте или при загрузке крупной модели, ошибка Context size has been exceeded, Model is unloaded, эндпоинт отвечает 404 или 200 с телом Unexpected endpoint, неверно определяется длина контекста. Содержит проверенные схемы эндпоинтов v1, параметр reasoning, особенности протокола и замеры на 30-35B.

Desko77/claude-code-skills-1c Agent Skills author: Desko77 MIT 1 file body ≈ 4 687 tokens Open the sourcegithub.com↗ analyzed 7 d ago

Справочник по HTTP-API LM Studio (сервер локальных моделей, обычно порт 1234).

As a process D 41/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

IntegrationFinancetype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
41/100
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

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 70Execution cost. Instruction body is 4687 tokens
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 10 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +3Description length 769: enough signal without eating the budget
  • +4Structure: 11 headings
  • +4Has examples (10 code blocks)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.