Conciseness

The ~20-line body is lean and dense: each numbered step is a compact directive ("Treat model input and output as untrusted. Escape output before HTML, shell, SQL, or templates.") with zero padding and no explanation of concepts Claude already knows. Every token earns its place.

Actionability

Concrete per-defect directives are given ("strip or quarantine instruction-like content from retrieved pages, emails, files, and API responses"; "token, time, and tool-call budgets with hard stops"; "prove spread on 3+ runs is within tolerance"), but no executable examples or concrete values (e.g., an escaping snippet, numeric budget defaults), leaving minor gaps rather than fully copy-paste-ready guidance.

Workflow Clarity

An 8-step numbered procedure is clearly laid out with an explicit "Exit criteria" validation gate ("The tester's AI suite passes, including injection cases, budgets trip correctly, and consistency is within tolerance"), but there is no explicit feedback loop for what to do when exit criteria fail, so it fits the most-checkpoints-present anchor rather than the full validate-fix-retry anchor.

Progressive Disclosure

This is a simple under-50-line skill with no need for external references, and the body is well organized into Procedure and Exit criteria sections; no bundle files exist or are referenced, so per the simple-skill guideline well-organized sections alone warrant the top score.

Specificity

The description enumerates a comprehensive defect taxonomy ("prompt injection, data leakage, unsafe output handling, excessive tool agency, runaway cost, inconsistent or ungrounded outputs") paired with matching remedies ("server-side permission checks, escaping, budgets, and grounding rules"), matching the multiple-concrete-actions anchor with no coverage gaps.

Completeness

It explicitly answers both "what" (fix defects using the listed techniques) and "when" ("Use for any model- or agent-driven feature bug"), a concrete trigger clause matching the explicit what-and-when anchor; the when-clause is explicit, not merely implied, so it does not fit the score-4 anchor.

Trigger Term Quality

Good natural keyword coverage ("prompt injection", "data leakage", "agent", "LLM", "runaway cost", "bug") that users would actually say, but a few common variations are missing (e.g., "hallucination", "jailbreak", "tool misuse"), so it fits the good-coverage-with-minor-gaps anchor rather than comprehensive synonym coverage.

Distinctiveness Conflict Risk

It carves a clear niche (remediation of model/agent feature defects) with distinct triggers, and explicitly distinguishes its role from the tester counterpart "qa-ai-agent-testing", giving minimal conflict risk with other skills.