What does this skill do, and when should you use it?
This skill is designed for testing chapter categorization and presents a structured overview of a four-page PDF document. It covers basic and advanced chapters plus getting started, installation, API usage, and troubleshooting topics. It also summarizes Bash and Python examples, code-quality scores, language statistics, and reference-file navigation. It is useful for validating documentation organization, but it is a small golden test fixture rather than a general-purpose PDF processor.
The skill documentation reports the document's four-page structure, groups content into basics, advanced material, and additional content, and identifies getting started, installation, API usage, and troubleshooting topics. It presents one Bash example and two Python examples, records code-block, image, and language counts, reports an average code-quality score, and links to chapter-specific reference files and an index.
- A developer testing whether a skill generator recognizes PDF chapter boundaries correctly.
- A documentation engineer reviewing extracted topics, page counts, and reference-file locations.
- A tool maintainer evaluating the quality metadata attached to extracted Bash and Python examples.
- A team validating navigation for getting started, installation, usage, and troubleshooting sections.
How do you install this skill?
- This SKILL.md appears to be a generated golden-test artifact rather than a standalone executable chapter-categorization skill.
- The claimed documentation/PDF conversion and conflict-detection capabilities are not directly evidenced by the assessed path.
- The long Python example is truncated with an ellipsis in SKILL.md and may not be executable as presented.
- Source, dependency, permission, failure-handling, and maintenance information is insufficient; publisher identity is treated as unknown per the brief.
The README states that the complete Skill Seekers collection can be installed with pip install skill-seekers, but it does not document installing this skill separately. The skill should be used as a directory containing SKILL.md; the source does not specify a destination path.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/yusufkaraaslan/Skill_Seekers.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/tests/golden/phase2/pdf_chapters" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- summarize this documentation by chapter
- find the installation and troubleshooting sections.
- Use when testing chapter categorization.
Enable the skill in an Agent Skills-compatible client and ask for chapter-focused tasks such as “summarize this documentation by chapter” or “find the installation and troubleshooting sections.” Its stated trigger description is “Use when testing chapter categorization.”
What are this skill's strengths and limitations?
- Provides a compact, structured view of chapters, topics, examples, statistics, and navigation.
- Includes both Bash and Python examples with quality scores.
- Identifies reference files and page ranges for follow-up reading.
- It is explicitly a golden test fixture for chapter categorization, so its scope is narrow.
- No standalone installation, configuration, or execution procedure is documented.
- One Python example is truncated and cannot be used as a complete implementation.
- The source does not demonstrate general PDF extraction or arbitrary-document processing.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| PDF Chapter Classification Skill this page | 31 · Not recommended | ★ 15k | 25d ago | MIT |
| Golden Word Documentation Skill | 30 · Not recommended | ★ 15k | 25d ago | MIT |
| Golden EPUB Keyword Classifier | 38 · Not recommended | ★ 15k | 25d ago | MIT |
| Keyword Categorization Test Docs | 29 · Not recommended | ★ 15k | 25d ago | MIT |
| Web Handbook Skill — Multi-Page Fixture | 41 · Not recommended | ★ 15k | 25d ago | MIT |
How did FollowSkills review this skill?
The skill only presents a PDF chapter summary, code snippets, and reference-file navigation. No malware, credential theft, or external side effects are visible, supporting a baseline trust score; however, it lacks permission scoping, user confirmation, data-flow disclosure, sensitive-data handling, rollback, and source-verification details, so points are deducted.
Page counts, categories, and reference paths are broadly consistent, and an error example is included; however, this is a static generated document with no execution procedure, input/output contract, exception handling, or diagnosable failure feedback. Key-path reproducibility is therefore unproven and points are deducted.
The trigger scenario, “testing chapter categorization,” is explicit, but the capability scope is very narrow. Input and output formats, non-fit cases, semantic trigger boundaries, Chinese-language handling, and mainland-China network reachability are not documented, so points are deducted.
The skill has basic naming, description, chapter overview, quick reference, code examples, and references navigation, with a reasonably clear structure; it lacks installation and dependency notes, parameter-stability guidance, FAQs, limitations, versioning, changelog, maintenance ownership, and update path, so points are deducted.
It can serve as a static index and summary of a four-page PDF, providing limited lookup value; however, it contains no operational instructions for chapter categorization, includes placeholder or low-value examples, and does not match the candidate description’s broader documentation-conversion and conflict-detection claims, so points are deducted.
PDF page numbers, chapter files, and image paths provide partial traceability; there is no independent execution evidence, committed test result covering this skill’s key paths, or cross-source corroboration. Under static review, only limited credit is justified.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →