outlines

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

Quality

67%

Does it follow best practices?

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Securityby

High

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tessl review fix ./skills/prompt-engineering/outlines/SKILL.md

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.

The body is a thorough, actionable reference with real bundle files and clear navigation, but it is verbose with repeated examples and inlines detail that duplicates the provided reference files. Tightening repetition and pushing duplicated detail into the references would improve it.

Suggestions

De-duplicate repeated examples (e.g., the classification snippet and the `outlines.models.transformers(...)` load line) by defining once and referring back, or by moving variants into references/examples.md.

Move the detailed Backend Configuration and Pydantic Integration sections into references/backends.md and references/json_generation.md respectively, keeping SKILL.md a concise overview that links out.

Make every code snippet self-contained (include imports and the model definition) so examples are fully copy-paste runnable without implicit context.

Dimension	Reasoning	Score
Conciseness	Mostly code-driven and reasonably efficient, but it repeats the same model-loading line ~15 times and re-states the classification example across Quick Start, Core Concepts, and Common Patterns, so it could be tightened.	3 / 5
Actionability	Code is largely executable and copy-paste ready across all generators, backends, and Pydantic patterns, but some snippets reuse an undefined `model` variable or omit imports, leaving minor gaps.	4 / 5
Workflow Clarity	The core load-model → build-generator → call-prompt action is shown clearly and repeatedly with a numbered 'How it works' sequence, though it is organized by feature rather than as an explicit end-to-end task flow.	4 / 5
Progressive Disclosure	A 'See Also' section clearly signals three real one-level-deep reference files, but substantial content that overlaps those references (Common Patterns, Backend Configuration, Pydantic Integration) is inlined in SKILL.md rather than split out.	3 / 5
	Total	14 / 20 Passed

Description

71%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.

The description is specific and names a clear, distinctive niche, but it omits any explicit 'when to use' trigger guidance, which caps its completeness. Adding a 'Use when...' clause with concrete user-facing triggers would raise the score.

Suggestions

Add an explicit 'Use when...' clause naming concrete user triggers (e.g., 'Use when generating guaranteed-valid JSON/XML from local models, or when the user needs type-safe structured outputs').

Include common synonyms users might say, such as 'JSON schema', 'structured output', or 'grammar-based generation', to broaden trigger-term coverage.

Keep the third-person voice and concrete action list as-is — they already support high specificity and distinctiveness.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — guaranteeing valid JSON/XML/code structure, using Pydantic models, supporting local models (Transformers, vLLM), and maximizing inference speed — giving comprehensive coverage.	5 / 5
Completeness	The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent trigger guidance, so completeness is capped at 3 per the rubric guideline.	3 / 5
Trigger Term Quality	Good natural keyword coverage (valid JSON, Pydantic models, local models, inference speed, structured generation) but missing common synonyms like 'schema' or 'structured output'.	4 / 5
Distinctiveness Conflict Risk	The named library (Outlines) and focused structured-generation/local-model niche make it mostly distinct, with only minor overlap risk against related tools like Instructor or Guidance.	4 / 5
	Total	16 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (653 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: OpenLAIR/dr-claw
Path: skills/prompt-engineering/outlines/SKILL.md
Commit: 4b35756

Reviewed: 1 day ago

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