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BC smoke-test

Health smoke tests + auto-fix for gbrain installs (and OpenClaw services when present). Run after machine/container restarts or whenever something seems broken. Tests critical services, auto-fixes bounded local issues, and reports worker topology without starting daemons. Extensible via user-defined test scripts in ~/.gbrain/smoke-tests.d/*.sh.

garrytan/gbrain Agent Skills author: garrytan MIT 1 file body ≈ 1 649 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Health smoke tests + auto-fix for gbrain installs (and OpenClaw services when present).

As a process C 57/100 · Has gaps — References files that are not bundled: ../conventions/agent-operator-protocol.md, scripts/smoke-test.sh

IntegrationSoftware developmentInfrastructureData and analyticstype 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%
75
Run on models
none yet
Process rating
C
57/100
Has gaps
References files that are not bundled: ../conventions/agent-operator-protocol.md, scripts/smoke-test.sh
Tools and files w 18
0
Failures and branches w 10
0
Result and completion w 14
60
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: gbrain

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: ../conventions/agent-operator-protocol.md
  • warning missing-ref reference to a missing file: scripts/smoke-test.sh
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "mutating"
  • note edit-residue the text marks something as outdated (lines 116): check that old rules are not kept next to new ones — the full check reads the text for contradictions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

Will not run. References files that are not bundled: ../conventions/agent-operator-protocol.md, scripts/smoke-test.sh
  • 0Tools and files. 2 referenced file(s) missing: ../conventions/agent-operator-protocol.md, scripts/smoke-test.sh
  • 0Failures and branches. Linear process with no failure handling
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 31 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1649 tokens
  • 100Running it twice. Mutating operations check current state
  • 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 346: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 31 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.