kaggle-learner

This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.

Quality

64%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/kaggle-learner/SKILL.md

Quality

Content

50%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 skill is a reasonably organized knowledge-base overview with a solid extraction standard, but it is held back by bilingual duplication, a black-box extraction step with no validation, and broken cv/multimodal directory references.

Suggestions

Remove the duplicated directory listing — keep either the Knowledge Categories table or the Additional Resources list, not both — and trim the generic 'Kaggle competitions are at the forefront...' overview to tighten conciseness.

Add a validation checkpoint to the extraction workflow (e.g., verify the new knowledge file exists under the correct domain directory and contains all required sections before considering extraction complete).

Fix the broken cv/ and multimodal/ references: either restore those directories from .archive/ so the advertised five categories exist, or remove them from the Knowledge Categories table and Additional Resources until populated.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient but includes generic padding ('Kaggle competitions are at the forefront of practical machine learning...'), bilingual duplication of the same content, and a duplicated directory listing (Knowledge Categories table repeats in Additional Resources), fitting the 'mostly efficient but could be tightened' anchor.	3 / 5
Actionability	A concrete required-content checklist and a markdown format template are provided, but the core extraction relies on a black-box 'kaggle-miner agent will extract' step with no concrete invocation, and no executable code lives in the body, matching the 'some concrete guidance but incomplete' anchor.	3 / 5
Workflow Clarity	The 'To learn from a competition' flow lists a 4-step sequence but has no validation or verification checkpoint (e.g., confirming knowledge was correctly extracted and placed), which caps it at the anchor for steps present with missing checkpoints.	3 / 5
Progressive Disclosure	Structure is a clean overview with one-level-deep per-domain references, but the body advertises five categories while only nlp/, tabular/, and time-series/ directories exist — the referenced cv/ and multimodal/ paths are broken (content is archived), matching the anchor for references present but incomplete/with organization gaps.	3 / 5
	Total	12 / 20 Passed

Description

78%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 well-constructed with explicit trigger guidance and a clear Kaggle niche, though its core capability phrasing ('provides access to extracted knowledge') is somewhat abstract rather than enumerating concrete operations.

Dimension	Reasoning	Score
Specificity	Names the domain and concrete trigger actions ('learn from', 'study', 'analyze') plus 'Provides access to extracted knowledge', but the core capability is a single abstract action with no further concrete operations, matching the anchor for domain + 1-2 actions without comprehensive coverage.	3 / 5
Completeness	Explicitly answers both 'what' (provides access to extracted knowledge from winning Kaggle solutions across five domains) and 'when' (concrete trigger phrases and URL mentions), matching the anchor for clear explicit what-and-when with concrete triggers.	5 / 5
Trigger Term Quality	Includes several natural user phrases ('learn from Kaggle', 'study Kaggle solutions', 'analyze Kaggle competitions', 'Kaggle competition URLs') with good coverage; a few natural synonyms are missing, so it sits above anchor 3 but below the comprehensive anchor 5.	4 / 5
Distinctiveness Conflict Risk	'Kaggle' is a clear niche with distinct triggers and low conflict risk, but the broad ML domain coverage (NLP, CV, etc.) creates minor overlap risk with general ML skills, placing it just below the minimal-conflict anchor 5.	4 / 5
	Total	16 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 4 missing, 10 deeper-than-1-level	Warning

	Total	14 / 16 Passed

Repository: Galaxy-Dawn/claude-scholar
Path: skills/kaggle-learner/SKILL.md
Commit: 2847aa1

Reviewed: 7 days ago

Table of Contents

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