AC agentic-security-review-skill
Create CompleteTech LLC security, safety, permissions, and production-readiness review artifacts for agentic development workflows, including risk intake, tool permissions, secrets handling, data exposure, prompt-injection testing, retrieval trust, approval gates, external actions, audit logging, model/provider configuration, retention, dependency risk, least privilege, launch blockers, rollback, incident response, escalation, red-team results, and security signoff. Use before production launch or whenever tools, data, credentials, integrations, retrieval sources, or external actions change.
Create CompleteTech LLC security, safety, permissions, and production-readiness review artifacts for agentic development workflows, including risk intake…
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 · 2
✓ No critical or high findings
Medium and low: 2
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low Risky intent
intent-offensive-securityREADME.md:88Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Not a compliance certification, penetration test, or legal approval.
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low Risky intent
intent-offensive-securitySKILL.md:28Offensive-security / dual-use content (legitimate for authorised testing; review intended use)This skill owns security, safety, permissions, data, credential, tool, and launch-risk review. Use it alongside discovery, proposal, or delivery when risk needs a dedicated artifact. It does not repla
Files scanned: 20. 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 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 6 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1727 tokens
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
- -5TODO / placeholder text left in the skill
- -31 of 3 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 598: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.