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lens

Operating manual for Lens — a reactive data canvas. Drive the pipeline by editing query.json (a node graph of source/SQL/semantic/chart nodes).

58

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./src-tauri/skills/data/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%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.

The content is a tight, well-structured operating manual with concrete executable examples and a clear collaboration sequence; it stays at 4 across dimensions due to minor gaps in from-scratch steps and explicit validation loops.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence (no explaining what SQL/CSV/DuckDB are); the only sizable block is a complete query.json example that earns its place, leaving minor trims possible rather than full anchor-5 leanness.

4 / 5

Actionability

A copy-paste-ready query.json plus concrete fields and constraints ({{id}} tokens, sampleLimit ≤200, no remote extensions) gives mostly executable guidance, with a minor gap in explicit from-scratch add-a-node steps.

4 / 5

Workflow Clarity

The sequence is clear — read query.json and last_result.json, edit, let the canvas recompute, read results — with the 'read state before changing' checkpoint present; editing a reactive canvas is not destructive/batch so the 3-cap does not apply, but an explicit validate/retry loop is absent.

4 / 5

Progressive Disclosure

No bundle files exist, so scoring is on the single self-contained doc, which is well-sectioned (graph, node kinds, how to collaborate) with content appropriately placed; minor organization room keeps it at anchor 4 rather than 5.

4 / 5

Total

16

/

20

Passed

Description

58%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.

The description is specific and clearly distinct but lacks an explicit 'when to use' trigger, which caps its completeness and trigger-term coverage at the midpoint.

Suggestions

Append a 'Use when …' clause naming concrete triggers (e.g., when the user is working in a Lens project, asks to build a data pipeline, or references query.json/last_result.json).

Add natural user-facing synonyms beyond the tool jargon — e.g., 'data pipeline', 'explore data', 'node graph' — so the description surfaces for everyday phrasings.

Spell out 2–3 concrete capabilities (e.g., add source/SQL/semantic/chart nodes, wire edges, read last_result.json) to lift specificity toward comprehensive coverage.

DimensionReasoningScore

Specificity

Names the domain and several concrete elements — 'editing query.json (a node graph of source/SQL/semantic/chart nodes)' — landing at 'several specific actions; minor gaps' rather than the comprehensive 5.

4 / 5

Completeness

It has a clear 'what' (operating manual for Lens, drive the pipeline by editing query.json) but no 'Use when…' trigger clause, which per the rubric caps completeness at 3.

3 / 5

Trigger Term Quality

Terms like 'Lens', 'reactive data canvas', 'node graph', and 'query.json' are relevant but largely jargon; common natural variations a user would say are missing, matching anchor 3.

3 / 5

Distinctiveness Conflict Risk

The named tool 'Lens — a reactive data canvas' carves a distinct niche with minimal conflict risk; it is mostly distinct rather than fully clear-niched (anchor 4) because trigger phrases are limited.

4 / 5

Total

14

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
tombrewsviews/BYOA
Reviewed

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