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interactive-viz

Multi-modal interactive data presentation for agentsociety-analysis — EDA bundle (PyGWalker, Plotly, sortable tables, eda_hub), plotly/altair claim charts, HTML tab surfaces. Use in explore, refine, and produce stages.

62

Quality

73%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./extension/skills/agentsociety-analysis/v1.0.0/support/interactive-viz/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

76%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 body is lean, well-structured, and actionable, but lacks validation checkpoints for its batch EDA workflow and points to three reference files that are not present in the bundle.

Suggestions

Add a verification step after the EDA run (e.g., confirm eda_hub.html was generated and spot-check a claim chart) to introduce a feedback loop for the batch operation.

Either include the referenced files under references/ (eda.md, charts.md, reports.md) or remove the dangling read-order pointers so navigation is not broken.

Fill in the single-mode command examples instead of using '...' ellipsis so each variant is directly executable.

DimensionReasoningScore

Conciseness

Lean and efficient throughout: short labeled sections, runnable command snippets, and a single import line, with no padding or explanation of concepts Claude already knows. Every section earns its place.

5 / 5

Actionability

Provides concrete, mostly copy-paste-ready commands and a real Python import, but the single-mode examples use '...' ellipsis and placeholder arguments (DB, DIR, WS, HID), leaving minor gaps for full execution.

4 / 5

Workflow Clarity

A rough sequence exists (stage triggers, read order, report embed) but there are no validation or verification checkpoints, and the EDA run is a batch operation over a DB — the rubric caps batch workflows without validation at 3.

3 / 5

Progressive Disclosure

The body is well-organized with a signaled one-level-deep read order, but it references references/eda.md, references/charts.md, and references/reports.md, none of which exist in the bundle — a real navigation gap that keeps it below 5.

4 / 5

Total

16

/

20

Passed

Description

71%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, distinct, and provides explicit trigger guidance, but its trigger terms are dominated by project-internal jargon rather than natural user phrasing, capping trigger-term quality at the midpoint.

Suggestions

Add natural-language trigger phrases users would actually say (e.g., 'interactive charts', 'data exploration dashboards', 'exploratory data analysis') alongside the stage names.

Replace or supplement the internal stage references ('explore, refine, produce stages') with concrete user-facing conditions so the 'when' is recognizable without project context.

DimensionReasoningScore

Specificity

Names several concrete tools and surfaces (PyGWalker, Plotly, sortable tables, eda_hub, plotly/altair claim charts, HTML tab surfaces), though 'presentation' is an umbrella rather than a list of discrete operations, so it falls just short of comprehensive.

4 / 5

Completeness

Both 'what' (multi-modal interactive data presentation with named tools) and 'when' ('Use in explore, refine, and produce stages') are present and explicit, but the 'when' uses internal stage names rather than concrete user-facing trigger phrases.

4 / 5

Trigger Term Quality

Relevant keywords exist but lean heavily on project-specific jargon ('agentsociety-analysis', 'eda_hub', 'explore/refine/produce stages', '§数据') rather than the natural phrases a user would actually say, missing common synonyms.

3 / 5

Distinctiveness Conflict Risk

Tightly scoped to agentsociety-analysis with distinctive named tooling and stage triggers, giving it a clear niche with minimal overlap risk against other skills.

5 / 5

Total

16

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 3 missing

Warning

Total

15

/

16

Passed

Repository
tsinghua-fib-lab/AgentSociety
Reviewed

Table of Contents

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