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ai-engineering

Reviews and guides LLM/AI application engineering — prompts, caching, RAG, agent loops and tools, resilience, model migration, evals, prompt-injection defence, and observability. Invoke with /ai-engineering for "review my prompt", "set up RAG", or "write evals".

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/quality/ai-engineering/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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 well-architected routing/index skill with genuinely strong workflow scaffolding (mode detection, pre-flight state statement, findings format, DoD checklist, consent guardrail), undermined by a broken delivery: the rule and template files it routes to are missing from the bundle, and the body carries duplicated and inline content that its own 'thin index' philosophy says should live in those files. Fixing the missing bundle files and de-duplicating the two area tables would move this to the top band.

Suggestions

Ship the referenced rules/*.md and templates/*.md files in the bundle (or remove the links and merge their essential content inline) — 15 of 17 referenced paths currently dangle, so 'Load the matched rule file(s)' steps cannot execute.

Delete the 'Required Reading by Area' section: its file column exactly duplicates the 'Area Routing' table and its own 'Load on demand — do not preload' note restates guidance already given, saving ~25 lines.

Trim 'Core Principles' and 'Anti-patterns' to a handful of one-line pointers into the relevant rule files, since full coverage is already claimed to live there and ~70 lines of inline rules contradict the 'thin index' design.

DimensionReasoningScore

Conciseness

The body is mostly tight (routing tables, one-line anti-patterns), but the 'Required Reading by Area' table restates the file column of the 'Area Routing' table (~25 duplicated lines), and the ~70 lines of Core Principles and Anti-patterns inline guidance that the file's own 'thin index' philosophy says lives in rules/*.md — more than the 'minor instances' an anchor-4 allows, though far from the padding of anchor 2.

3 / 5

Actionability

Guidance is concrete and executable in form: exact file paths, a literal 'Mode: review / Areas: … / Targets: src/agents/triage.ts (system prompt at L24-78)' output block, a What/Rule/Fix findings format with 'path:line' and 'code snippet when ≤ 10 lines', and named Skill() invocations ('Skill("otel-instrumentation", …)'). Not 5 because no example finding or filled template is shown, and the load-rules steps depend on files absent from the bundle; not 3 because within the body every step is specific rather than pseudocode.

4 / 5

Workflow Clarity

Each of the three modes has a numbered sequence with checkpoints: 'State the detected mode and the area(s) in scope before continuing', a 'Definition of Done' checklist, a 'Top 3 fixes' prioritization step, and the consent guardrail 'Do not edit the file in review mode unless the user asks for fixes' — plus an error-recovery fallback ('If neither skill is in the available-skills list, fall back to the inline guidance'). Not 5 because there is no mid-workflow verification that the loaded rules actually cover the target, and the OTEL fallback is the only recovery path.

4 / 5

Progressive Disclosure

The design is anchor-5 quality — 'This SKILL.md is a thin index. Detailed rules live in rules/*.md and load on demand' with well-signaled one-level-deep links — but scored against the actual bundle, 15 of the 17 referenced paths (all 13 rules/*.md and all 4 templates/*.md) do not exist; only references/primary-sources.md and references/recent-changes.md are present. The on-demand loading pattern the whole skill depends on cannot function as delivered, which is at least as severe as anchor 3's 'references present but not clearly signaled'.

3 / 5

Total

14

/

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 description: third-person, concrete on both what and when, with literal user-utterance triggers and a clearly distinct niche. Its only real weakness is that the three quoted trigger phrases cover just a third of the nine advertised areas, and a few natural synonyms (retrieval, guardrails, tracing) are absent.

DimensionReasoningScore

Specificity

'Reviews and guides LLM/AI application engineering — prompts, caching, RAG, agent loops and tools, resilience, model migration, evals, prompt-injection defence, and observability' names a comprehensive set of capability areas, but the actions themselves are the generic pair 'reviews'/'guides' rather than multiple distinct concrete verbs like the anchor-5 'extract, fill forms, merge' pattern — several specific actions with minor gaps.

4 / 5

Completeness

Both halves are explicit: what = 'Reviews and guides LLM/AI application engineering — [nine areas]', and when = 'Invoke with /ai-engineering for "review my prompt", "set up RAG", or "write evals"'. Not 5 because the concrete trigger phrases cover only 3 of the nine enumerated areas — a user asking about retries, model migration, or tracing gets no trigger cue — which is exactly anchor 4's 'when could be more explicit or specific'.

4 / 5

Trigger Term Quality

Natural user phrasings are present verbatim ('review my prompt', 'set up RAG', 'write evals') alongside strong keywords (RAG, evals, caching, agent loops, model migration). Not 5 because common synonyms users would say are missing — 'retrieval', 'guardrails', 'tracing', 'token cost', 'structured outputs' — leaving a few natural terms uncovered.

4 / 5

Distinctiveness Conflict Risk

It claims a clear niche — LLM/AI application engineering across prompts, RAG, agents, evals, resilience, and observability — with unambiguous triggers ('review my prompt', 'set up RAG') that no adjacent skill (PDF work, general code review, commit messages) would claim; conflict risk is minimal.

5 / 5

Total

17

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 34 missing

Warning

Total

13

/

16

Passed

Repository

mthines/agent-skills

Path

skills/quality/ai-engineering/SKILL.md

Reviewed

Table of Contents

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