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negentropy-lens

A decision-support framework that evaluates systems, architectures, and strategies through the entropy (decay) vs negentropy (growth) lens, while surfacing tacit knowledge gaps. Use this skill whenever the user is making architecture decisions, evaluating system designs, reviewing technical approaches, choosing between options, auditing existing systems, or planning strategies. Also trigger when the user explicitly asks to "apply the negentropy lens", mentions "entropy", "negentropy", "tacit knowledge", "knowledge engine", or "flip the switch". Nudge activation when you detect the user is at a decision point — even if they haven't asked for this lens — by briefly noting the entropic/negentropic dimension before proceeding.

64

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

57%

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

A well-organized conceptual framework with clear sequencing and an appropriate single-level reference to a real bundle file. It is held back by prose that is somewhat more evocative than lean, guidance that is qualitative rather than executable, and a decision workflow that lacks explicit validation checkpoints or feedback loops.

Suggestions

Trim rhetorical restatements ('There is no neutral. Inaction is entropic.', 'This is non-negotiable') to reduce tokens without losing the framework's substance.

Add a concrete output template (e.g., a per-component assessment table with columns for Entropic/Negentropic indicators, Tacit-knowledge gaps, and Recommendation) so the guidance is executable rather than purely descriptive.

Insert an explicit validation/feedback step into the decision process — e.g., after Phase 2 or Phase 5, a checkpoint that re-checks classifications against surfaced tacit assumptions and loops back — to give the workflow real error-recovery.

DimensionReasoningScore

Conciseness

The body is mostly efficient and well-organized, but portions restate concepts and lean on evocative prose ('Every decision either accelerates entropy or drives negentropy. There is no neutral. Inaction is entropic.') and explanatory phrasing ('This is non-negotiable', 'These are the most dangerous') that add tokens without adding guidance Claude couldn't derive; it could be tightened.

2 / 3

Actionability

It provides concrete guidance — numbered phases, named indicators, and specific probing questions — but the guidance is conceptual/qualitative rather than executable: there is no code, command, concrete output template, or copy-paste-ready artifact, and 'Adapt the format to context' leaves the actual output structure underspecified.

2 / 3

Workflow Clarity

The 5-phase decision process is clearly sequenced (Map → Diagnose → Surface Tacit Layer → Evaluate → Challenge), but there are no validation checkpoints or feedback loops: nothing tells Claude how to confirm a classification is correct before proceeding, and Phase 5 ('Challenge') is presented as a terminal step rather than a loop back to earlier phases.

2 / 3

Progressive Disclosure

The SKILL.md is a self-contained overview with a single one-level-deep reference, 'references/origin-essay.md', which exists as a real bundle file and is clearly signaled in two places (the intro and the content-creation section); content is appropriately kept inline for a concept framework with no deeper nesting.

3 / 3

Total

9

/

12

Passed

Description

92%

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, well-structured description that explicitly covers what the skill does, when to use it, and natural trigger keywords, with distinctive branded phrases. Its only weakness is breadth: the generic decision-making triggers ('choosing between options', 'making architecture decisions') could overlap with other advisory or review skills, modestly raising conflict risk.

Suggestions

Tighten the 'when' clause so generic triggers like 'choosing between options' are qualified to decision points where entropy/negentropy or tacit-knowledge framing actually applies, reducing overlap with general decision-making or code-review skills.

Lead the description with the most distinctive capability (the entropy/negentropy + tacit-knowledge lens) before the broad 'making architecture decisions' list, so the skill's niche is immediately clear.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'evaluates systems, architectures, and strategies', 'making architecture decisions, evaluating system designs, reviewing technical approaches, choosing between options, auditing existing systems, or planning strategies' — naming the domain and several specific capabilities.

3 / 3

Completeness

It answers both 'what' (a decision-support framework evaluating systems through the entropy/negentropy lens while surfacing tacit knowledge gaps) and 'when' with an explicit 'Use this skill whenever...' clause plus keyword triggers and a nudge-activation condition.

3 / 3

Trigger Term Quality

It includes natural trigger phrases a user would actually say — 'architecture decisions', 'evaluating system designs', 'reviewing technical approaches', plus the explicit keyword triggers 'entropy', 'negentropy', 'tacit knowledge', 'knowledge engine', and 'flip the switch'.

3 / 3

Distinctiveness Conflict Risk

The domain is fairly specific (entropy/negentropy + tacit-knowledge lens) with distinctive triggers like 'flip the switch' and 'knowledge engine', but the broad triggers 'making architecture decisions', 'evaluating system designs', and 'choosing between options' could plausibly overlap with general code-review or decision-making skills, risking activation for the wrong skill.

2 / 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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
bencium/bencium-marketplace
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.