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industry-friction-radar

Proactive Bleeding-Edge research loop using a strict 3-step abstraction protocol to extract engine-category friction points without importing framework-category bias or stealing code. Triggers: Use this skill when executing periodic "horizon scans" for the Dream Pipeline, researching external solutions to deeply complex engine-level friction points, or evaluating JS ecosystem trends.

66

Quality

78%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./.agents/skills/industry-friction-radar/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-3

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

The body is appropriately concise and well-structured as a pointer to a single real reference file, but it provides almost no actionable or workflow detail inline — the entire procedure is offloaded. This is acceptable progressive disclosure but leaves the body itself thin on guidance.

Suggestions

Add a one-line summary of the 3-step protocol (Ingest → Extract friction → Native ideation) so the body gives Claude an executable skeleton before it opens the reference.

Name the tools the workflow requires (search_web, ideation-sandbox) inline so the body is actionable without first loading the reference file.

DimensionReasoningScore

Conciseness

The body is a single sentence that defers all detail to a reference file; it assumes Claude's competence and contains no padding, matching the lean-and-efficient anchor.

3 / 3

Actionability

It gives one concrete, executable instruction (use the `view_file` tool to read a specific path) but delegates the entire actual procedure to another file, so key operational details are missing from the body itself.

2 / 3

Workflow Clarity

The multi-step workflow (a 3-step abstraction protocol per the reference) lives entirely in the referenced file; the body shows no sequenced steps or validation checkpoints, only a redirect to 'read and strictly adhere to' another file.

2 / 3

Progressive Disclosure

The body is a clean overview that points to a single one-level-deep, clearly signaled reference (industry-friction-radar-workflow.md) that exists in ./references/, matching the well-signaled-overview anchor.

3 / 3

Total

10

/

12

Passed

Description

85%Weight 40%Scale 1-3

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 is specific, complete, and clearly distinct, with both capabilities and explicit trigger guidance. Its main weakness is trigger-term quality: the keywords lean heavily on internal Neo/Dream Pipeline jargon rather than language a user would naturally say.

Suggestions

Reframe triggers in user-natural language (e.g., 'when researching bleeding-edge JS/ECMAScript features', 'when surveying external solutions to performance bottlenecks') alongside the internal terms so they match what a user would actually say.

Add common keyword variations (e.g., 'native JS features', 'WebGPU', 'Worker paradigms', 'SharedArrayBuffer') to broaden natural-term coverage.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'strict 3-step abstraction protocol to extract engine-category friction points', 'executing periodic horizon scans', 'researching external solutions', 'evaluating JS ecosystem trends' — matching the multi-action anchor.

3 / 3

Completeness

Explicitly answers both what ('3-step abstraction protocol to extract engine-category friction points') and when via a 'Triggers: Use this skill when...' clause, satisfying the dual what-and-when anchor.

3 / 3

Trigger Term Quality

It has an explicit 'Triggers: Use this skill when...' clause but the keywords are project-internal jargon ('Dream Pipeline', 'engine-level friction points', 'horizon scans') rather than natural terms a user would spontaneously say, so coverage of common variations is incomplete.

2 / 3

Distinctiveness Conflict Risk

A clear niche ('Bleeding-Edge research loop', 'engine-category friction points', 'Dream Pipeline') with distinct, narrow triggers that are unlikely to fire for unrelated skills.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
neomjs/neo
Reviewed

Table of Contents

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