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golden-jupyter-topics

Use when testing the golden_jupyter_topics golden build

Quality

52%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./tests/golden/phase2/jupyter_topics/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

47%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 content is an auto-generated notebook scrape: reasonably well-structured with real reference files for progressive disclosure, but it lacks a coherent actionable workflow and includes redundant statistics and a truncated, low-value code block. It reads as a reference index more than an actionable skill.

Suggestions

Remove the duplicated Notebook Statistics / Total Sections content and the truncated long code example to improve token efficiency.

Replace or contextualize the broken code example ('%timeit broken()') with an executable, meaningful snippet.

Add a short, sequenced workflow (e.g. locate section in index.md -> open the matching reference file -> reproduce the cell) with a verification checkpoint so reproduction is actionable.

DimensionReasoningScore

Conciseness

The body is mostly compact metadata and code snippets without explaining concepts Claude already knows, but it duplicates statistics (Total Sections appears in two sections) and wastes tokens on a truncated giant code block ('x0'...'x3...').

3 / 5

Actionability

Concrete code fragments exist (pip install, pandas read_csv) but they are illustrative notebook scrape artifacts rather than coherent task guidance, and one example ('%timeit broken()') is non-functional, leaving key details missing.

3 / 5

Workflow Clarity

There is no real sequence or validation checkpoints; only a rough 'When to Use' list of activities (understand, reference, reproduce, review) with no defined process or steps to follow.

2 / 5

Progressive Disclosure

A clear overview body points to real one-level-deep reference files with a dedicated Navigation section ('See references/index.md for complete notebook structure'), though some content that duplicates the references (statistics, code examples) is inlined rather than split out.

4 / 5

Total

12

/

20

Passed

Description

32%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 thin: it provides a trigger condition but no statement of what the skill actually does, and its keywords are internal jargon rather than natural user phrasing. It is distinctive only because its named target is very niche.

Suggestions

Add an explicit 'what' clause stating concrete actions the skill performs, e.g. 'Reference and reproduce the golden_jupyter_topics notebook analysis workflow.'

Replace jargon ('golden build') with natural trigger terms a user would actually say, such as 'golden_jupyter_topics notebook', 'reproduce notebook results', or 'reference notebook analysis'.

Tighten completeness by combining a concrete capability statement with the 'Use when' trigger in a single sentence.

DimensionReasoningScore

Specificity

The description names a domain ('testing the golden_jupyter_topics golden build') but offers no concrete actions beyond the generic verb 'testing', matching the anchor that names a domain with minimal or generic actions.

2 / 5

Completeness

Only a 'when' clause is present ('Use when testing the golden_jupyter_topics golden build') with no clear 'what' describing what the skill does, matching the anchor where only 'when' is present without 'what'.

2 / 5

Trigger Term Quality

It contains only one generic keyword ('testing') plus internal jargon ('golden_jupyter_topics', 'golden build') that users would not naturally say, missing the natural phrases a user would actually utter.

2 / 5

Distinctiveness Conflict Risk

The highly specific named target ('golden_jupyter_topics golden build') gives it a clear niche with minimal conflict risk, though the thin, jargon-heavy description leaves minor overlap/ambiguity with related testing skills.

4 / 5

Total

10

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

yusufkaraaslan/Skill_Seekers

Path

tests/golden/phase2/jupyter_topics/SKILL.md

Reviewed

Table of Contents

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