Conciseness

The ~65-line router is lean: every section is instruction ("Read [manifest.yaml](manifest.yaml)", "State the detected value in one short line", "Do **not** read every fragment in static/"), with no explanations of concepts Claude already knows and no padding. It assumes competence throughout, matching the anchor-5 example; there is no over-explanation to trim that would justify 4.

Actionability

The guidance names concrete values (five source_format options with detection meanings) and a priority order, but the executable targets are missing: "Read [manifest.yaml](manifest.yaml)", the `always_load` files, `core/principles.md`/`core/workflow.md`/`core/output-contract.md`, the `static/` fragments, and `../nature-shared/core/terminology-ledger.md` do not exist in this bundle, so an agent following step 1 fails immediately. It is above 2 (there is specific, structured guidance, not high-level hints) but below 4 because key execution details are unresolvable as shipped; the bundled `scripts/validate_reader_math.py` is also never wired in.

Workflow Clarity

Steps 1–5 are clearly sequenced with an explicit mid-process checkpoint ("State the detected value in one short line to the user before processing, so they can correct you cheaply") and a fallback rule for multi-format sources and constrained inputs ("still create a draft reader and label missing pages… Do not switch to summary mode"). Not 5 because the "pre-response verification checklist" is delegated to `core/output-contract.md`, which is absent from the bundle, leaving the final validation step implicit; the operation is not destructive/batch so no cap applies.

Progressive Disclosure

The on-demand reference table is well designed — figure-extraction.md, output-spec.md, equation-handling.md, and grounding-rules.md all exist, are one level deep, and are clearly signaled by need. However, scoring against the actual bundle: the primary navigation layer the skill is built around (manifest.yaml, always_load/core files, static/ fragments) is absent, `references/article-anatomy.md` is orphaned (never referenced), and `scripts/` is undiscoverable from the body. This lands at 3 — good structure undermined by broken navigation paths — rather than 4/5, but above 2 since existing references are properly signaled, not buried.

Specificity

"Create source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations" names the deliverable plus its concrete components (aligned text, figures, tables, equations), and handling of excerpts/questions is mentioned — several specific actions with a minor gap (no mention of how inputs like PDFs are ingested). It sits below 5 ("multiple specific concrete actions; comprehensive coverage") because the action list is centered on one verb, and above 3 because more than 1–2 concrete specifics are given.

Completeness

It explicitly answers both: the "what" ("Create source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations") and the "when" ("Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper"), with concrete trigger phrases. This matches the anchor-5 example structure directly, so neither 4 nor a lower score fits.

Trigger Term Quality

"Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper" includes natural phrases a user would say, including Chinese synonyms for the core use cases. Not 5 because common English variations ("translate this paper", "read this paper", format terms like PDF/arXiv) are missing; not 3 because several genuinely natural trigger terms are present, not generic jargon.

Distinctiveness Conflict Risk

"Chinese-English paper readers", "全文翻译", "论文精读", and "source-grounded" carve out a clear niche with distinct triggers that virtually no generic PDF, translation, or summarization skill would claim. Minor overlap risk with general translation skills exists but is below the level that would justify 4, since the bilingual reader/精读 framing is unmistakable.