Content
88%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
An excellent, highly actionable body: every recipe is executable as written, the decision flow (outline → scan → grep → pages) is explicitly ordered, and failure modes have concrete recovery paths. The only deductions are minor verbosity (the licensing aside) and a single-file layout that forgoes any one-level-deep reference split for its ~240 lines of recipes.
Suggestions
Trim or relocate the AGPL/PyMuPDF licensing paragraph (lines ~53-57) — it is background knowledge tangential to using the helpers, or could live in a one-line note.
Consider moving one or two of the longer recipes (e.g., the figure-crop and exhaustive-extraction recipes) into a references/ file with a clearly signaled link, keeping SKILL.md as a tighter overview with the helper table and setup.
Drop rhetorical framing like "Nothing you read vanishes: it is ordinary text and ordinary files" in the intro; the operational facts already carry the point.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes competence — no space is spent explaining what a PDF is or how Python works, and details like "pillow does the PNG encoding for mode='image'; it is not pulled in by the pypdfium2 wheel" are genuinely non-obvious. It sits at 4 rather than 5 because of minor trimmable asides, notably the AGPL/PyMuPDF licensing paragraph and editorializing like "Nothing you read vanishes: it is ordinary text and ordinary files". | 4 / 5 |
Actionability | Every recipe ships copy-paste-ready, complete code: the exec loader line, the multi-range pdf_pages pull with file-write and byte-count print, the outline printer, the pdf_scan shortlist loop, the high-DPI render plus pillow crop sequence, and a working DOI regex with a de-duplication comprehension. This matches the 5 anchor ("Fully executable; copy-paste ready... specific examples cover the common cases") rather than 4, which would imply gaps in the code. | 5 / 5 |
Workflow Clarity | Sequencing is explicit and ordered ("Recipe — navigate by outline (try this first)", "fall through to pdf_scan", "skip the narrowing" when short), and each recipe carries its own feedback loops: "If a helper is 'not defined', you haven't exec'd kernel.py yet — go back and run the line above", "broaden top_k if the shortlist looks thin", "if the PDF has none it returns []... build the outline yourself", and mode="auto" re-rendering for scanned pages. This matches the 5 anchor's explicit error-recovery loops; the 4 anchor's "minor validation gaps" understates the coverage, and the destructive/batch cap does not apply since the skill is read-only. | 5 / 5 |
Progressive Disclosure | Structure is good: a helper-selection table up front, one section per recipe, and clearly signaled setup pointing to the single external kernel.py ("exec(open(...kernel.py).read())"). No bundle files exist (no references/, scripts/, or assets/), and at ~240 lines all recipes live inline in SKILL.md — appropriately placed overall, but the figure/extract recipes could plausibly live in one-level-deep reference files, which is the 4 anchor's "minor organization gaps" rather than the 5 anchor's well-signaled reference split. | 4 / 5 |
Total | 18 / 20 Passed |