reducing-entropy

Use when evaluating designs, reviewing code, or refactoring - measures success by total code in the final codebase, not effort to get there. Bias toward deletion.

Quality

54%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./reducing-entropy/SKILL.md

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a well-crafted philosophical/decision-making skill that is concise, memorable, and well-structured. Its main strength is token efficiency — it communicates a clear mental model through sharp examples and anti-patterns. Its weakness is that actionability could be improved with a concrete before/after evaluation example, and the progressive disclosure to reference files lacks enough context for the reader to understand what's available without exploring the filesystem.

Suggestions

Add a brief concrete example showing the evaluation process applied to a real scenario (e.g., 'Given a PR that refactors 3 files into 7 with better separation: count lines before (180) vs after (240) → reject').

List the available reference mindsets in the SKILL.md with one-line descriptions so Claude can select without needing to list and read files first.

Dimension	Reasoning	Score
Conciseness	Every section earns its place. The content is lean, uses concrete examples (50 lines deleting 200 = net win), avoids explaining concepts Claude already knows, and communicates the philosophy through sharp, memorable phrases rather than verbose explanations.	3 / 3
Actionability	The three questions framework and red flags provide concrete decision-making guidance, but this is a judgment/mindset skill rather than a code skill, so the lack of executable code is acceptable. However, it could be more actionable with a concrete example walkthrough (e.g., before/after code comparison showing the evaluation process in action).	2 / 3
Workflow Clarity	The workflow is clear: load a reference mindset first, then apply three sequential questions, watch for red flags, and check exceptions. For a decision-making/evaluation skill (not a destructive batch operation), this sequence is well-defined with the explicit gate ('Do not proceed until you've done this') serving as a validation checkpoint.	3 / 3
Progressive Disclosure	The skill references `references/` directory and `adding-reference-mindsets.md` for deeper content, which is good progressive disclosure structure. However, no bundle files were provided to verify these references exist, and the references are not clearly signaled with descriptions of what each contains — the user is told to list and read frontmatter, but the SKILL.md itself doesn't summarize what's available.	2 / 3
	Total	10 / 12 Passed

Description

32%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description reads more like a coding philosophy or principle ('bias toward deletion', 'measures success by total code') than a skill description. It lacks concrete actions and specific capabilities, making it unclear what the skill actually does beyond applying a minimalist mindset. The trigger terms are too broad and would likely conflict with many other code-related skills.

Suggestions

Add specific concrete actions the skill performs, e.g., 'Identifies and removes dead code, simplifies over-engineered abstractions, consolidates duplicate logic, and reduces overall codebase size.'

Narrow the trigger terms to reduce conflict risk, e.g., 'Use when the user asks to reduce code complexity, eliminate dead code, simplify implementations, or minimize codebase size.'

Clarify what distinguishes this from a general code review skill - is it specifically about code minimization? If so, make that the clear focus rather than listing broad activities like 'reviewing code'.

Dimension	Reasoning	Score
Specificity	The description mentions 'evaluating designs, reviewing code, or refactoring' but these are broad categories, not concrete actions. There are no specific capabilities listed like 'delete unused functions', 'identify dead code', or 'simplify complex methods'. The phrase 'measures success by total code in the final codebase' is a philosophy, not an action.	1 / 3
Completeness	It has a 'Use when' clause covering when to apply the skill (evaluating designs, reviewing code, refactoring), but the 'what does this do' part is very weak - it describes a philosophy ('bias toward deletion', 'measures success by total code') rather than concrete capabilities or outputs.	2 / 3
Trigger Term Quality	Contains some relevant keywords like 'designs', 'reviewing code', 'refactoring', and 'deletion' that users might naturally use. However, it's missing common variations and more specific terms like 'dead code', 'cleanup', 'simplify', 'reduce complexity', 'code review', or 'technical debt'.	2 / 3
Distinctiveness Conflict Risk	Terms like 'reviewing code' and 'refactoring' are extremely broad and would overlap with virtually any code-related skill. 'Evaluating designs' could conflict with UI/UX skills, architecture skills, or general code review skills. The only distinguishing element is the deletion bias philosophy, which is not a clear niche.	1 / 3
	Total	6 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: joshuadavidthomas/agent-skills
Commit: 4c9cb62

Reviewed: 19 days ago

Table of Contents

Discovery Implementation Validation

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