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CD validate

Freshly judge exact subject content against bead or caller acceptance, optionally persist verdict.v2 for a declared consumer, and stop. Triggers: "validate", "independently validate", "vibe".

boshu2/agentops Agent Skills author: boshu2 5 files · 4 scripts body ≈ 1 508 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Freshly judge exact subject content against bead or caller acceptance, optionally persist verdict.v2 for a declared consumer, and stop. Triggers: "validate"…

As a process D 46/100 · Unfinished process — References files that are not bundled: scripts/test-ci-deterministic-gates.sh

AnalyzerSoftware developmentAI 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
D
46/100
Unfinished process
References files that are not bundled: scripts/test-ci-deterministic-gates.sh
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
  2. 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: 5. 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")
  • warning missing-ref reference to a missing file: scripts/test-ci-deterministic-gates.sh
  • note frontmatter-key unknown frontmatter key "practices"
  • note frontmatter-key unknown frontmatter key "hexagonal_role"
  • note frontmatter-key unknown frontmatter key "consumes"
  • note frontmatter-key unknown frontmatter key "produces"
  • note frontmatter-key unknown frontmatter key "context_rel"
  • note frontmatter-key unknown frontmatter key "skill_api_version"
  • note frontmatter-key unknown frontmatter key "output_contract"

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: scripts/test-ci-deterministic-gates.sh
  • 0Tools and files. 1 referenced file(s) missing: scripts/test-ci-deterministic-gates.sh
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 12 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1508 tokens
  • 100Running it twice. Mutating operations check current state
  • low The response is described with custom markup (5 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 191: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 12 items

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