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ai-development-guide

Applies technical decision criteria, anti-pattern detection, debugging, and quality gates for backend and frontend code. Use when implementing, reviewing, or diagnosing code, code smells, failures, or implementation completeness.

Quality

79%

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tessl review fix ./skills/ai-development-guide/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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-structured instruction-only guide with genuinely actionable checklists, decision trees, and an explicit impact-analysis workflow with validation gates. Its weaknesses are token efficiency — restating known principles (SRP, DRY, YAGNI, 5 Whys) and verbose policy passages — and a monolithic main body that underuses the reference-file pattern it already demonstrates with frontend.md.

Suggestions

Remove or compress restatements of concepts Claude already knows — e.g., the SRP/DRY annotations in the anti-pattern list, "5 Whys", "Be conscious of YAGNI", and "Measure before optimizing" — keeping only the project-specific decision rules around them.

Tighten the wordiest passages, such as the Value-First Engineering complexity paragraph and the Scope Expansion bullets, into short directive rules; the current multi-clause sentences cost many tokens without adding decision value.

Move well-bounded topic blocks (e.g., Fail-Fast Fallback Design Principles or the Impact Analysis report template) into additional one-level-deep reference files like the existing frontend.md, keeping SKILL.md as a lean overview with read-when conditions.

DimensionReasoningScore

Conciseness

The body is dense and mostly project-specific policy, but it restates concepts Claude already knows ("Violates Single Responsibility Principle (SRP)", "Violates DRY principle", "5 Whys", "Be conscious of YAGNI", "Measure before optimizing") and includes wordy passages such as "Judge total complexity across every activated surface: user decisions, settings, modes, concepts, outputs...". Not 2 because there is no tutorial-style padding or basic-concept explanation; not 4 because several sections need tightening and the known-principle restatements are unnecessary.

3 / 5

Actionability

For an instruction-only skill it provides concrete, executable guidance: a 4-step "Before Implementing Any Fallback" checklist, five specific error-masking review triggers, a 3-stage impact analysis with a fill-in report template, a decision tree ("Required by the requested change? No → Preserve unless the change proves it obsolete"), and defined quality-check categories; the AVOID/PREFERRED pseudocode is explicitly justified as language-agnostic. Not 5 because some directives remain abstract ("Inspect until the evidence identifies the lowest-total-complexity solution").

4 / 5

Workflow Clarity

Multi-step processes are clearly sequenced: the 3-stage impact analysis (Discovery → Understanding → Identification) has an explicit gate ("Proceed when discovery and understanding cover the accepted outcome..."), and the quality workflow has ordering rules and a completion criterion ("Completion requires every applicable configured check to pass"). Not 5 because the quality workflow lacks an explicit fix-and-retry feedback loop; not 3 because validation checkpoints are explicit, not implicit.

4 / 5

Progressive Disclosure

The single bundle file, references/frontend.md, exists and is referenced one level deep with a clear read-when condition ("read when implementing, reviewing, fixing, or diagnosing frontend code"), and frontend.md contains no nested references. Not 5 because the ~250-line body is a dense wall of policy across many topics where more content could be split into reference files; not 3 because structure and signaling are otherwise good.

4 / 5

Total

15

/

20

Passed

Description

80%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 with an explicit third-person capability statement and a concrete "Use when" trigger clause covering multiple natural phrasings. Its main weakness is breadth: triggering on any code implementation, review, or diagnosis invites overlap with more specialized coding skills.

DimensionReasoningScore

Specificity

Lists several specific capability areas — "technical decision criteria, anti-pattern detection, debugging, and quality gates" — for a named domain ("backend and frontend code"), though these are action categories rather than fully concrete operations like the anchor-5 examples. Not 3 because it covers more than 1-2 actions; not 5 because the phrasing stays one level of abstraction above concrete operations.

4 / 5

Completeness

Explicitly answers both parts: the "what" ("Applies technical decision criteria, anti-pattern detection, debugging, and quality gates for backend and frontend code") and the "when" via a concrete "Use when implementing, reviewing, or diagnosing code, code smells, failures, or implementation completeness" clause. Both are present with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Includes natural phrases users would say — "implementing, reviewing, or diagnosing code, code smells, failures" — with good coverage. Not 5 because common variations like "bugs", "refactor", or "code review" are missing; not 3 because the present keywords go beyond a bare domain mention.

4 / 5

Distinctiveness Conflict Risk

"Use when implementing... code" would trigger for nearly any coding task, creating real overlap risk with code-review and debugging skills. Not 2 because "code smells", "implementation completeness", and "quality gates" give it some niche specificity; not 4 because the trigger scope is still very broad.

3 / 5

Total

16

/

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

shinpr/claude-code-workflows

Path

skills/ai-development-guide/SKILL.md

Reviewed

Table of Contents

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