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hugging-face-dataset-viewer

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

62

Quality

74%

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SecuritybySnyk

Low

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tessl review fix ./skills/hugging-face-dataset-viewer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

64%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 solid API reference skill that provides concrete, actionable endpoint patterns and useful curl/npx examples. Its main weaknesses are scope creep (dataset creation/upload in a read-only viewer skill), missing error-handling/validation checkpoints in workflows, and lack of progressive disclosure via supporting files. The filter predicate syntax and search query examples are notably absent.

Suggestions

Add a concrete example for `/filter` showing actual `where` predicate syntax (e.g., `where=column1>5`) and `/search` with a real query string.

Add error-handling guidance: what to do when `/is-valid` returns false, when responses include `partial: true`, or when 401/403 is returned for gated datasets.

Consider removing or splitting the 'Creating and Uploading Datasets' section into a separate file, as it contradicts the skill's stated read-only scope.

Remove the generic 'When to Use' footer—it adds no actionable information.

DimensionReasoningScore

Conciseness

Generally efficient with minimal over-explanation. The API endpoint listing is compact and useful. Minor verbosity in the 'Creating and Uploading Datasets' section which goes beyond the stated skill scope (read-only Dataset Viewer API), and the 'When to Use' footer is a filler sentence that adds no value.

4 / 5

Actionability

Provides concrete curl commands, npx invocations, and specific endpoint URL patterns that are copy-paste ready. Minor gaps: the `/filter` predicate syntax is not illustrated with an example (just mentions 'predicate syntax in `where`'), and the `/search` endpoint lacks a concrete example query.

4 / 5

Workflow Clarity

The core workflow lists a clear 6-step sequence for exploration, and the pagination pattern is well-illustrated. However, there are no validation checkpoints or error-handling guidance (e.g., what to do if `/is-valid` returns false, how to handle 401/403 for gated datasets, or what to do when `partial` is true). The upload section introduces a destructive-adjacent operation (creating/uploading datasets) without verification beyond a single curl check.

3 / 5

Progressive Disclosure

Content is organized into logical sections with clear headers, but everything is inlined in a single file. The SQL export section, the upload workflows, and the parquet querying details could benefit from being split into separate referenced files. No bundle files exist to offload detail, and no references to external docs are provided.

3 / 5

Total

14

/

20

Passed

Description

83%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.

This is a strong skill description that clearly enumerates specific API operations and anchors itself to the Hugging Face Dataset Viewer API, making it highly distinctive. The 'when' guidance is present but could be slightly more explicit with user-facing trigger phrases and common synonyms. Overall, it would perform well in a multi-skill selection scenario.

Suggestions

Add common user-facing synonyms like 'HF datasets', 'browse dataset rows', or 'explore Hugging Face data' to improve trigger term coverage.

Expand the 'when' clause slightly, e.g., 'Use when the user asks about querying, browsing, or downloading data from Hugging Face datasets via the Dataset Viewer API.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics. This is comprehensive coverage of the API's capabilities.

5 / 5

Completeness

The 'what' is clearly answered with the list of actions. The 'when' is present via 'Use this skill for Hugging Face Dataset Viewer API workflows', but it could be more explicit about user-facing trigger phrases (e.g., 'when the user asks about exploring datasets on Hugging Face' or 'when querying HF dataset contents').

4 / 5

Trigger Term Quality

Includes strong natural keywords like 'Hugging Face', 'Dataset Viewer API', 'parquet', 'rows', 'filters', 'search text', 'metadata', 'statistics'. Missing some synonyms users might say like 'HF datasets', 'dataset info', 'browse dataset', or 'dataset API'.

4 / 5

Distinctiveness Conflict Risk

Highly distinctive — 'Hugging Face Dataset Viewer API' is a very specific niche with clear, unique triggers like 'parquet URLs', 'subset/split metadata', and the Hugging Face brand name. Minimal risk of conflicting with other skills.

5 / 5

Total

18

/

20

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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