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BC auto-review-loop-llm

Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".

wanshuiyin/Auto-claude-code-research-in-sleep Agent Skills author: wanshuiyin MIT 1 file body ≈ 1 745 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Autonomous research review loop using any OpenAI-compatible LLM API.

As a process C 53/100 · Has gaps — References files that are not bundled: ../../shared-references/output-versioning.md, ../../shared-references/output-manifest.md, ../../shared-references/output-language.md

IntegrationAI 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
References files that are not bundled: ../../shared-references/output-versioning.md, ../../shared-references/output-manifest.md, ../../shared-references/output-language.md
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: Auto-claude-code-research-in-sleep

How to improve

  1. The text references files that are not there: add them or drop the references.
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 missing-ref reference to a missing file: ../../shared-references/output-versioning.md
  • warning missing-ref reference to a missing file: ../../shared-references/output-manifest.md
  • warning missing-ref reference to a missing file: ../../shared-references/output-language.md
  • note edit-residue the text marks something as outdated (lines 12, 102): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 53/100

Will not run. References files that are not bundled: ../../shared-references/output-versioning.md, ../../shared-references/output-manifest.md, ../../shared-references/output-language.md
  • 0Tools and files. 3 referenced file(s) missing: ../../shared-references/output-versioning.md, ../../shared-references/output-manifest.md, ../../shared-references/output-language.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 17 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1745 tokens
  • 100Progress reporting. Reports progress

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)
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 181: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 17 items
  • +3Output format is stated explicitly
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.