Conciseness

Several sections open by defining concepts Claude already knows — "Prompt injection occurs when adversarial input overrides the model's system prompt", "Model inversion attacks reconstruct training data from model outputs", "Data poisoning attacks insert malicious examples into training data" — and the ~365-line body inlines reference-style material (full risk matrices, guardrail catalogs) that could be tightened or split out. This is mostly efficient but includes unnecessary explanation, matching anchor 3; it is not lean throughout (score 4) because the definition sentences and duplicated ATLAS tables both add avoidable tokens.

Actionability

The guidance is fully executable: copy-paste-ready scanner invocations with real flags (--target-type, --access-level, --scope, --authorized, --json, --list-patterns), a concrete test-file JSON format, and a runnable CI/CD gate snippet using jq on output fields (.overall_risk, .findings[].finding_type) that all verified present in scripts/ai_threat_scanner.py. This matches the top anchor — commands cover the common cases and are ready to run — rather than leaving minor gaps (score 4).

Workflow Clarity

Three clearly sequenced workflows with explicit decision checkpoints driven by exit codes ("Exit code 2 = block deployment; fix critical findings first") and a CI gate that validates the report and blocks on critical risk. The fix-and-rescan feedback loop after remediation is implied by the decision text but never shown as an explicit re-run/re-validate step, so this fits anchor 4 (most checkpoints present, minor validation gaps) rather than anchor 5 (explicit feedback loops for error recovery).

Progressive Disclosure

Structure is good: a table of contents, a clearly signaled one-level-deep reference ("Full ATLAS technique coverage reference: references/atlas-coverage.md", verified to exist and substantive), and a real scripts/ entry point, matching the actual bundle layout. Substantial reference-style content — the model-inversion and data-poisoning risk matrices and the guardrail pattern catalogs — is inlined in SKILL.md rather than split into references, which fits anchor 4 (good structure, minor organization gaps) rather than anchor 5 (content appropriately split into an overview-plus-references shape).

Specificity

The description enumerates concrete, specific actions — "MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring" — across a comprehensive list of threat types ("prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse"). It lists multiple specific concrete actions with comprehensive coverage, matching the top anchor; it is not merely naming a domain with generic actions (score 3) nor leaving minor gaps (score 4).

Completeness

Both halves are explicit: the trigger clause "Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, ..." answers when with concrete trigger conditions, and "Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring" answers what. This clearly matches the anchor where both what and when are answered with concrete trigger phrases; the score-4 anchor ("when could be more explicit or specific") does not fit since the when clause is specific.

Trigger Term Quality

Natural terms a security reviewer would actually say are present — "prompt injection", "jailbreak", "model inversion", "data poisoning", "agent tool abuse", "MITRE ATLAS" — giving good keyword coverage. A few common variations are missing (e.g., "LLM security", "AI red teaming", "adversarial robustness testing"), so it falls just below the comprehensive-with-synonyms top anchor rather than clearly matching it.

Distinctiveness Conflict Risk

The description carves out a clear niche — security assessment of AI/ML systems and LLM agents specifically — with distinct triggers (prompt injection, jailbreak, ATLAS mapping) that would not naturally fire a general application-security or threat-hunting skill. Minimal conflict risk, matching the top anchor; score 4 ("minor overlap risk with closely related skills") is too cautious given the domain-specific vocabulary.