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axiom-audit-foundation-models

Use when the user mentions Foundation Models review, on-device AI audit, LanguageModelSession issues, or @Generable/guardrail problems — including missing availability checks, manual JSON parsing, and guardrail handling.

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable audit skill with an exemplary phase structure, verification checkpoints, false-positive guards, and concrete grep/fix pairs throughout. Its weaknesses are modest: some repetition of the OS 26/27 migration explanation across sections and a monolithic length that inlines all 14 patterns rather than splitting any detail out.

DimensionReasoningScore

Conciseness

The body is dense with non-inferable specifics (UnavailableReason cases, OS27 error-migration details, evaluation-framework wiring) and avoids teaching basics, but the OS 26/27 migration story is told roughly three times ('Search BOTH error spellings...', Pattern 4, Pattern 14) and Patterns 4 and 5 repeat the same generic-catch grep. Minor instances of repetition that could be trimmed — anchor 4, not 5.

4 / 5

Actionability

Every pattern ships literal, copy-paste-ready grep regexes ('import\s+FoundationModels', 'SystemLanguageModel\.default\.availability'), complete executable Swift fix snippets ('guard SystemLanguageModel.default.availability == .available else {...}', '.disabled(session.isResponding)'), and specific per-match verification instructions. Matches anchor 5 ('fully executable; copy-paste ready; covers common cases').

5 / 5

Workflow Clarity

Five clearly sequenced phases with explicit validation checkpoints: 'Present this map in the output before proceeding', 'For every grep match, use Read to verify the surrounding context before reporting', plus Output Limits and a False Positives section forming a review checklist. A built-in feedback loop (grep recall → Read verify) matches anchor 5; the audit is read-only, so no destructive-operation cap applies.

5 / 5

Progressive Disclosure

References are clearly signaled and one level deep ('See `axiom-ai (skills/foundation-models-ref.md)` for the full migration table'), and the migration table itself is appropriately deferred rather than inlined. However, no bundle files exist in this skill, all 14 detection patterns are inlined in a ~485-line monolith, and the referenced paths live in a different bundle ('axiom-ai') so their existence cannot be verified here — anchor 4 ('good structure; references mostly clear; minor organization gaps'), not 5.

4 / 5

Total

18

/

20

Passed

Description

78%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, trigger-first description with concrete API-level keywords and low conflict risk. Its main weakness is structural: the 'what' is embedded in the when-clause instead of stated as a leading capability statement, and a few natural trigger terms (notably 'Apple Intelligence') are missing.

Suggestions

Lead with a direct capability statement before the trigger clause, e.g., 'Audits Apple Foundation Models / Apple Intelligence integrations for availability, session, guardrail, and structured-output issues.'

Add 'Apple Intelligence' and 'iOS 26'/'macOS 26' as trigger terms — the body relies on them but the description omits them, and users are likely to say 'Apple Intelligence' rather than 'Foundation Models'.

DimensionReasoningScore

Specificity

Names the domain ('Foundation Models review', 'on-device AI audit') and several concrete detection targets ('missing availability checks, manual JSON parsing, and guardrail handling'), but coverage is not comprehensive — session lifecycle, concurrency, and evaluation-suite detection from the body are absent. Anchor 4 ('lists several specific actions; minor gaps') fits; not 5 because the action list is incomplete, not 3 because more than 1-2 concrete actions are given.

4 / 5

Completeness

The 'when' is explicit and concrete ('Use when the user mentions Foundation Models review, on-device AI audit, LanguageModelSession issues...') and the 'what' is present via the 'including missing availability checks, manual JSON parsing, and guardrail handling' list, but there is no direct leading capability statement (e.g., 'Audits Foundation Models code for...'). Fits anchor 4 ('both what and when; one could be more explicit') rather than 5.

4 / 5

Trigger Term Quality

Includes natural user phrasing plus specific API keywords: 'Foundation Models review', 'on-device AI audit', 'LanguageModelSession issues', '@Generable/guardrail problems'. A few common natural terms are missing — notably 'Apple Intelligence' (used heavily in the body) and 'Apple' platform qualifiers — so it fits anchor 4, not 5.

4 / 5

Distinctiveness Conflict Risk

Apple-specific API names ('LanguageModelSession', '@Generable', 'guardrail', 'Foundation Models') carve out a clear niche with distinct triggers and minimal overlap with other skills, matching anchor 5.

5 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

CharlesWiltgen/Axiom

Path

axiom-codex/skills/axiom-audit-foundation-models/SKILL.md

Reviewed

Table of Contents

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