AD pr-autocheck
Automated post-submit checks for an AI code-review platform. Use when a new pull request is submitted (or on demand) to run a code review, validate service health, combine both into one report, and sync the result to a team Discord channel via webhook. Triggers on requests like "run PR autocheck", "review this PR and post to Discord", "automate PR checks", or wiring a CI/post-submit hook.
Automated post-submit checks for an AI code-review platform.
As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
exfil-webhook-urlSKILL.md:54Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)DISCORD_WEBHOOK_URL="https://discord.com/api/webhooks/..." \
placeholder
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 48/100
- 0Result and completion. Does not say what the result is
- 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
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 75Steps. 3 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 492 tokens
- 100Running it twice. No mutating operations
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
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 391: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 3 items
- +4Has examples (2 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.