full-output-enforcement
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
75
68%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Critical
Do not install without reviewing
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/output-skill/SKILL.mdQuality
Discovery
52%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 has a clear structure with both 'what' and 'when' components, which is good for completeness. However, it relies heavily on technical LLM jargon that users wouldn't naturally use, and the trigger scope ('any task requiring exhaustive, unabridged output') is overly broad, risking false matches. The description would benefit significantly from user-facing natural language trigger terms.
Suggestions
Replace technical jargon with natural user language: instead of 'LLM truncation behavior' and 'placeholder patterns', use terms like 'no placeholders', 'don't skip code', 'write the full file', 'complete implementation', '// rest of code'.
Narrow the 'when' clause from the overly broad 'any task requiring exhaustive, unabridged output' to more specific triggers like 'Use when the user asks for complete code without shortcuts, complains about truncated output, or requests no placeholder comments like // ... rest of code'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (LLM output behavior) and some actions like 'enforces complete code generation', 'bans placeholder patterns', and 'handles token-limit splits', but these are more behavioral constraints than concrete, discrete actions a user would recognize. | 2 / 3 |
Completeness | Clearly answers both what ('overrides default LLM truncation behavior, enforces complete code generation, bans placeholder patterns, handles token-limit splits') and when ('Apply to any task requiring exhaustive, unabridged output'), with an explicit trigger clause. | 3 / 3 |
Trigger Term Quality | Uses technical jargon like 'LLM truncation behavior', 'placeholder patterns', and 'token-limit splits' that users would rarely naturally say. Users are more likely to say things like 'don't skip code', 'write the full file', 'no placeholders', or 'complete output'. | 1 / 3 |
Distinctiveness Conflict Risk | The concept of 'complete code generation' and 'no placeholders' is somewhat distinct, but 'any task requiring exhaustive, unabridged output' is very broad and could overlap with many coding or writing skills. The scope is unclear enough to cause potential conflicts. | 2 / 3 |
Total | 8 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A strong, well-structured skill that provides clear, actionable constraints for enforcing complete output. The banned patterns list is concrete and comprehensive, the workflow is well-sequenced with validation steps, and the token-limit handling is practical. Minor redundancy between the cross-check step and the Quick Check section prevents a perfect conciseness score.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient but has some redundancy — the 'Quick Check' section largely restates the cross-check step and banned patterns list. Some phrasing like 'A partial output is a broken output' is motivational rather than instructional. Overall reasonably tight but could be tightened. | 2 / 3 |
Actionability | Provides a concrete, exhaustive list of banned patterns, a specific execution process with numbered steps, and an exact template for handling token-limit pauses. The guidance is specific and directly usable — Claude knows exactly what to do and what not to do. | 3 / 3 |
Workflow Clarity | The three-step execution process (Scope → Build → Cross-check) is clearly sequenced with an explicit validation checkpoint (cross-check deliverable count). The token-limit handling includes a clean feedback loop (pause → continue → resume). The Quick Check serves as a final validation gate. | 3 / 3 |
Progressive Disclosure | This is a focused, single-purpose skill under 50 lines of substantive content. It is well-organized into clearly labeled sections (Baseline, Banned Patterns, Execution Process, Handling Long Outputs, Quick Check) with no need for external references. Structure is clean and navigable. | 3 / 3 |
Total | 11 / 12 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 — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- Leonxlnx/taste-skill
- Commit
840b46b
- Reviewed
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