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sn-infographic

Generates professional infographics with various layout types and visual styles. Analyzes content, recommends layout and style, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", or "可视化".

72

Quality

92%

Does it follow best practices?

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SecuritybySnyk

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The risk profile of this skill

SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

A highly actionable, well-sequenced skill body with executable code, explicit validation checkpoints, and a clean one-level-deep reference structure verified against the actual bundle. Its only real weakness is verbosity from restated guard explanations and padded scope preambles.

Suggestions

Deduplicate the JSON-envelope status-guard prose (the '.result is null / use extract_json.py / return Error Flow' explanation is restated nearly verbatim in Step 1, Step 2.0, and Step 2.3) — state the pattern once and reference it.

Tighten the Step 1 'Scope (do not over-read the step name)' preamble; the anti-misinterpretation guidance is useful but currently padded and could be a short bullet list.

Add references/prompt-writing-rules.md (which exists in the bundle) to the References section so all present files are discoverable, or remove it if unused.

DimensionReasoningScore

Conciseness

The body is mostly efficient and assumes Claude's competence — no generic concept explanations — but it is ~525 lines with redundancy: the JSON-envelope status-guard / literal-'null' / extract_json.py explanation is restated nearly verbatim in Step 1, Step 2.0, and Step 2.3, and the 'Scope (do not over-read the step name)' preamble is padded. This is above a 1 (it earns its tokens operationally) but could be tightened, matching the 'mostly efficient but includes some unnecessary explanation' anchor.

2 / 3

Actionability

Provides fully executable bash snippets (sn_agent_runner.py invocations with exact flags), concrete parameter tables, and a precise JSON return contract with literal substitution rules — copy-paste ready with no pseudocode, matching the top anchor.

3 / 3

Workflow Clarity

Steps are clearly sequenced (Step 0→4) with explicit validation checkpoints — `.status == ok` guards, Error Flow returns, an early-termination check, and a mandatory evaluation call — providing the feedback loops the rubric rewards for fragile/batch operations.

3 / 3

Progressive Disclosure

The body is an orchestration overview pointing to one-level-deep references (references/*.md, references/layouts/, references/styles/) that are all verified to exist (87 layouts, 66 styles matching the stated counts), with a clear References section and explicit 'read only the selected file' guidance; navigation is easy and references are well signaled.

3 / 3

Total

11

/

12

Passed

Description

100%

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 description that concisely states concrete capabilities and gives explicit, natural-language (bilingual) trigger guidance. It answers both what and when without fluff or over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Generates professional infographics', 'Analyzes content', 'recommends layout and style', and 'generates publication-ready infographics' — each tied to a specific output, matching the 'Lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both 'what' (generates/analyzes/recommends infographics) and 'when' via the explicit 'Use when user asks to create…' clause, hitting the top anchor.

3 / 3

Trigger Term Quality

Includes natural bilingual trigger terms a user would say — 'infographic', '信息图', 'visual summary', '可视化' — giving good coverage of common variations rather than technical jargon.

3 / 3

Distinctiveness Conflict Risk

The infographic niche with distinct bilingual triggers is clearly distinguishable from general image or document skills and unlikely to fire for the wrong skill.

3 / 3

Total

12

/

12

Passed

Validation

68%

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

Validation11 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (555 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

11

/

16

Passed

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

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