AB agent-security-hardening
Security hardening patterns for production AI agents. Covers prompt injection defense (7 rules), data boundary enforcement, read-only defaults for external integrations, WAL protocol for data integrity, health check scripts, integrity gates, rule escalation ladder, and session memory security. Use when hardening agent deployments against adversarial inputs, data leaks, or operational failures. NOT for network security, infrastructure hardening, or penetration testing.
As a process B 66/100 · Nearly there — weak spots: 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
-
low Risky intent
intent-offensive-securitySKILL.md:3Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)description: 'Security hardening patterns for production AI agents. Covers prompt injection defense (7 rules), data boundary enforcement, read-only defaults for external integrations, WAL protocol for
quoted -
low Risky intent
intent-offensive-securitySKILL.md:202Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Privilege escalation (requests for access the current context doesn't have)
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6178 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 66/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 16 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 6178 tokens
- 100Steps. 27 steps
- 100Failures and branches. 5 branches, has a failure section
- 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 10 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
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 472: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 27 items
- +3Output format is stated explicitly
- +4Has examples (24 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.