AC self-improving-security
Captures vulnerabilities, misconfigurations, access control violations, compliance gaps, incident response patterns, and threat intelligence to enable continuous security improvement. Use when: (1) A CVE or vulnerability is discovered, (2) Secrets are exposed in logs or output, (3) Access control violations or unauthorized access attempts occur, (4) Compliance audit findings or gaps are identified, (5) Security misconfigurations are found in infrastructure or applications, (6) Incident response procedures are executed or improved, (7) Threat intelligence is gathered from advisories or pen test results.
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
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low Risky intent
intent-offensive-securitySKILL.md:378Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Privilege escalation indicators
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low Risky intent
intent-offensive-securitySKILL.md:601Offensive-security / dual-use content (legitimate for authorised testing; review intended use)3. **Identify access issues** — unauthorized access, privilege escalation, broken auth
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low Risky intent
intent-offensive-securitySKILL.md:630Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)- `auth bypass|privilege escalation|tls|ssl|cors misconfiguration`
quoted
Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6054 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 17 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Failures and branches. 4 branches
- 70Execution cost. Instruction body is 6054 tokens
- 85Steps. 119 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 20 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 609: enough signal without eating the budget
- +4Structure: 54 headings
- +3Step-by-step instructions: 119 items
- +4Has examples (18 code blocks)
- +4Reference files are cited in the instructions (2 of 3)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.