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devtu-code-optimization

Code quality patterns and guidelines for ToolUniverse tool development. Apply when writing, fixing, or refactoring tool Python code in the ToolUniverse project. Encodes lessons from 80+ debug rounds. Use alongside devtu-fix-tool and devtu-self-evolve. Triggers: implementing tool fixes, writing new tool classes, reviewing tool code quality, checking schema correctness, looking up API-specific bug fixes.

72

Quality

90%

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SKILL.md
Quality
Evals
Security

Quality

Content

93%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.

An exemplary lean skill body: a concrete pre-commit validation checklist, a well-designed routing table that defers all detail to two real one-level-deep reference files, and terse executable git rules. The only gap is the absence of explicit error-recovery guidance for when validation steps fail.

DimensionReasoningScore

Conciseness

The body is entirely dense, project-specific signal: a 9-item checklist of exact commands, a signal-to-reference mapping table, and terse git rules. Nothing explains concepts Claude already knows, and there is no padding — every token earns its place.

5 / 5

Actionability

Nearly every line is executable: `ruff check src/tooluniverse/<file>.py`, `python -m tooluniverse.cli run <Tool> '<real_args_json>'`, `python3 -c "import json; json.load(open('f.json'))"`, `gh pr view <N> --json mergeable`. Placeholders like `<file>.py` are per-target parameterization, not pseudocode, and the checklist covers the common pre-commit cases.

5 / 5

Workflow Clarity

The Pre-Commit Checklist provides an explicit validation sequence (schema → tests → syntax → registry → lint → import → run) and the git section has a real checkpoint ("must be MERGEABLE before done") with a safe variant (force-with-lease, never main). It falls short of 5 because error-recovery feedback loops are implicit — nothing says what to do when the rebase conflicts, a checklist item fails, or the PR is not mergeable.

4 / 5

Progressive Disclosure

The body is a pure overview: the Key Fix Categories table maps each bug signal to a named section in a reference file, and a References section lists both files (which exist, and contain no nested second-level references). Content is appropriately split with one-level-deep, clearly signaled navigation — matches the anchor-5 structure.

5 / 5

Total

19

/

20

Passed

Description

83%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 that clearly states what the skill covers and when to use it, with an explicit trigger list and sibling-skill boundaries. Its only weaknesses are a slightly abstract opening phrase and trigger keywords that miss a few natural synonym phrasings.

DimensionReasoningScore

Specificity

Names the domain ("ToolUniverse tool development", "tool Python code") and lists several concrete actions: "writing, fixing, or refactoring tool Python code", "checking schema correctness", "looking up API-specific bug fixes", "writing new tool classes", "reviewing tool code quality". It falls just short of the 5 anchor because the opening "Code quality patterns and guidelines" frames the what somewhat abstractly, a minor gap in coverage.

4 / 5

Completeness

Explicitly answers what ("Code quality patterns and guidelines for ToolUniverse tool development") and when with two concrete trigger formulations: "Apply when writing, fixing, or refactoring tool Python code in the ToolUniverse project" and "Triggers: implementing tool fixes, writing new tool classes, reviewing tool code quality...". This matches the anchor-5 exemplar structure of a clear what followed by explicit when-clauses.

5 / 5

Trigger Term Quality

The trigger list is natural and matches what a user on this project would say ("implementing tool fixes", "writing new tool classes", "checking schema correctness", "looking up API-specific bug fixes"). It sits between the 4 and 5 anchors: coverage is good but misses common variations/synonyms a user might phrase differently (e.g., "debugging a tool", "linting", "schema validation errors").

4 / 5

Distinctiveness Conflict Risk

The ToolUniverse project scoping and explicit sibling-skill delineation ("Use alongside devtu-fix-tool and devtu-self-evolve") give it a clear niche. It is not a 5 because trigger phrases like "writing new tool classes" and "reviewing tool code quality" could plausibly match generic Python code-quality or refactoring skills if the project name is absent from the user's phrasing — minor overlap risk with closely related skills.

4 / 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

mims-harvard/ToolUniverse

Path

skills/devtu-code-optimization/SKILL.md

Reviewed

Table of Contents

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