AF publish-skill
Prepare, safety-review, version, commit, and publish local Codex skills through a GitHub-backed release flow and ClawHub CLI. Use when the user asks to host, publish, release, update, package, audit, or automate publication of a Codex skill, including GitHub repository setup, ClawHub `clawhub skill publish <path>`, patch updates, GitHub Actions with `CLAWHUB_TOKEN`, release notes, or pre-publish security checks.
Prepare, safety-review, version, commit, and publish local Codex skills through a GitHub-backed release flow and ClawHub CLI.
As a process F 37/100 · Will not run — References files that are not bundled: scripts/review_skill.py
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/review_skill.py
Process rating: all ten parameters 37/100
- 0Tools and files. 1 referenced file(s) missing: scripts/review_skill.py
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 21 mutating operations with no state check
- 40Consistency. Frontmatter name (publish-skill) differs from the folder (jichengkai-publish-skill)
- 70When it triggers. States when to use, but not when not to
- 100Steps. 38 steps
- 100Execution cost. Instruction body is 1037 tokens
- low The response is described with custom markup (6 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
- +5Description has no quoted example phrases that should trigger the skill
- +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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 415: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 38 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.