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charting

Selects the right chart type and visualization library for React/Next.js (web) and Expo/React Native (mobile) data visualization tasks, then applies accessibility and anti-pattern guardrails. Maps data shape and intent (comparison, composition, distribution, relationship, evolution, flow, geographic, hierarchical) to a recommended chart, then to a recommended library based on platform, dataset size, and design system. Defers cross-cutting UI concerns (contrast, touch targets, typography, copy) to the `ux` skill rather than restating them. Triggers on: "what chart should I use", "visualize this data", "build a chart", "build a dashboard", "data visualization", "pick a chart library", "graph this", "/charting".

72

Quality

90%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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, highly actionable advisory workflow with a clear phase sequence, concrete decision tables, and a disciplined hand-off story for sibling skills. Its two real weaknesses are broken progressive disclosure — almost every `rules/*.md` file the body instructs Claude to load is absent from the bundle — and moderate redundancy between the Quick reference, Files, and Behavioural rules sections.

Suggestions

Ship the 11 missing `rules/*.md` files (or remove the references and inline the essential rules): Phase 2–4 instruct 'Load `rules/chart-type-selection.md`', 'Load `rules/anti-patterns.md`', etc., but no `rules/` directory exists in the bundle, so the core workflow cannot execute as written.

Add an explicit validation checkpoint at the end of the workflow (e.g. 'Before responding, verify the answer fills the Output format template and every Accessibility check cites a named anti-pattern or WCAG criterion') to close the workflow-clarity gap.

Trim duplication between the Quick reference tables, the Files section, and Behavioural rules — e.g. keep the intent→chart table only as a pointer to `rules/chart-type-selection.md`, since Behavioural rules 2/5/8 already restate Phase 4/5 guidance and the Hard rules.

DimensionReasoningScore

Conciseness

The body assumes Claude's competence (no explanations of what charts or libraries are), and instruction lines like "Ask — in **one** batched message — only the answers you cannot infer from context" are tight. But there is duplicated material: the Quick reference tables restate content flagged as "full table in `rules/chart-type-selection.md`", the Files section re-describes files already linked in the Phase 4 table, and Behavioural rules 2/5/8 restate Phase 4/5 guidance and Hard rules. That repetition is what keeps it at level 4 ('minor instances of over-explanation that could be trimmed') rather than 5.

4 / 5

Actionability

Guidance is fully concrete for an advisory skill: a copy-paste output-format template, a signal→file loading table, an intent→chart decision table, a platform→library table with named defaults ("shadcn charts (Recharts under the hood) or Tremor", "Apache ECharts (Canvas)", "Victory Native XL (Skia)"), and numeric hard rules ("Pie charts: ≤ 5 slices", "Categorical palette: ≤ 8 categories"). Per the rubric's instruction-only note, absence of code is not penalized when guidance is this specific — the common cases are covered concretely.

5 / 5

Workflow Clarity

Six phases are clearly sequenced (discover intent → select chart → select library → apply guardrails → point at examples → hand off), with batching rules in Phase 1 ("If the user already supplied any of these, do not ask again") and a hard guard in Phase 2 ("Never recommend a chart whose intent does not match the user's question"). This is an advisory skill with no destructive/batch operations, so no validation cap applies; what keeps it at 4 rather than 5 is the absence of any explicit verification checkpoint (e.g., confirming the assembled answer matches the Output format before responding).

4 / 5

Progressive Disclosure

The design is strong — a lean overview with clearly signaled one-level-deep references, an always-on vs load-on-demand split, and a signal table mapping request cues to exact files — which alone would suggest 5. But scored against the actual bundle as the rubric requires, 10 of the 11 referenced rule files (e.g. `rules/chart-type-selection.md`, `rules/anti-patterns.md`, `rules/performance.md`) do not exist; only `references/galleries-and-examples.md` is present. Phases 2–4 instruct loading files that are missing, so the disclosure structure is broken in delivery. Not level 2 because the inlined content (quick-reference tables) partially covers the missing detail and the references that do exist are clearly signaled and well organized.

3 / 5

Total

16

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20

Passed

Description

100%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.

An exemplary description: third-person, concrete, and comprehensive on both capabilities and triggers, with explicit trigger phrases and explicit deferral boundaries that demarcate it from sibling skills. No fluff or over-claims; every clause carries information.

DimensionReasoningScore

Specificity

Quotes like "Selects the right chart type and visualization library", "applies accessibility and anti-pattern guardrails", and "Maps data shape and intent (comparison, composition, distribution, relationship, evolution, flow, geographic, hierarchical) to a recommended chart, then to a recommended library" list multiple concrete actions with full enumeration of the intent taxonomy, platforms, and selection factors (platform, dataset size, design system). Coverage is comprehensive and in third person ("Selects", "Maps", "Defers", "Triggers"), matching the level-5 anchor; nothing is generic or padded.

5 / 5

Completeness

The 'what' is explicit (chart-type and library selection for React/Next.js web and Expo/React Native mobile, plus accessibility and anti-pattern guardrails) and the 'when' is explicit and concrete: "Triggers on: 'what chart should I use', 'visualize this data', ...". This mirrors the level-5 anchor pattern of both what and when stated with concrete trigger phrases; level 4 would leave the 'when' less specific.

5 / 5

Trigger Term Quality

Explicit trigger phrases — "what chart should I use", "visualize this data", "build a chart", "build a dashboard", "data visualization", "pick a chart library", "graph this", "/charting" — cover the natural synonyms users would say for this domain (chart, graph, visualize, dashboard, library) plus the slash command. Not level 4 because the synonyms are comprehensive for a domain with no relevant file extensions; these are phrases a user would naturally say verbatim.

5 / 5

Distinctiveness Conflict Risk

A clear niche (chart-type + library selection for React/React-Native dataviz) with distinct triggers, and it actively reduces overlap risk by scoping out siblings: "Defers cross-cutting UI concerns (contrast, touch targets, typography, copy) to the `ux` skill rather than restating them". Level 4 ('minor overlap risk with closely related skills') is surpassed because the boundaries against adjacent skills are drawn explicitly rather than left implicit.

5 / 5

Total

20

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
mthines/agent-skills
Reviewed

Table of Contents

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