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CD architecture-evolution-coordinator

(no description)

ClawHub Agent Skills author: whoisme007 v1.0.0 MIT-0 6 files body ≈ 1 546 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

ProcedureGitHubGmailSoftware developmentAI and agentsResearchtype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
C
74/100
safety, quality, tests
Safety 60%
100
Quality 40%
34
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • note frontmatter-key unknown frontmatter key "layer"
  • note frontmatter-key unknown frontmatter key "function_type"
  • note frontmatter-key unknown frontmatter key "health"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • note frontmatter-key unknown frontmatter key "issue"

Process rating: all ten parameters 41/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (git, python) that frontmatter does not declare
  • 100Steps. 71 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1546 tokens
  • low 15 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -228 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 71 items
  • +4Has examples (11 code blocks)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 34.

External checks

ClawHub: suspicious
Review before installing: the skill is coherent for architecture maintenance, but it describes fixed-address email reporting, asks for credentials, runs local workspace code, and uses hard-coded health results.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026