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research-lookup

Compile current scholarly evidence for a scientific manuscript or research brief. Use when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source verification, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.

68

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is research-lookup in K-Dense-AI/scientific-agent-skills

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

Excellent actionability and workflow clarity — every step has executable commands, verification checkpoints, and error-recovery loops, and the reference quality rules read as a genuine checklist. The two weaknesses are mild routing-rule redundancy and a monolithic single-file layout that inlines backend details and artifact specs that belong in separate reference files.

Suggestions

Move the backend compatibility details ("Important compatibility behavior", "Output compatibility") and the per-backend sections (Chat, Perplexity, deep research) into a references/backends.md and keep only the routing table in SKILL.md.

Extract the packet artifact descriptions (step 4) into a references/packet-format.md linked from the workflow step, leaving SKILL.md a concise overview.

De-duplicate the routing rules stated in both the "Parallel-first routing" table and the per-backend sections — state each routing rule once and cross-reference it.

DimensionReasoningScore

Conciseness

The body is almost entirely operational content — commands, flags, packet file listings, quality rules, failure handling — with no explanations of concepts Claude already knows. It does not reach 5 because routing rules are repeated across the "Parallel-first routing" table, "Important compatibility behavior", and each backend section, and the "Output compatibility" field list plus citation-fetching instructions could be trimmed or moved. It stays above 3 because nearly every section carries non-obvious, task-specific detail.

4 / 5

Actionability

Every workflow step ships a copy-paste-ready command with real flags (--academic, --target-references 60, --context-file, --packet-dir, --force-backend, --extract-limit), a concrete JSON context example, the exact packet artifact filenames, pinned install commands, and named failure remedies. This matches the fully-executable anchor covering the common cases.

5 / 5

Workflow Clarity

The five-step manuscript workflow is clearly sequenced with explicit checkpoints: extraction verification in step 3, "inspect coverage.json; refine the question, date range, terminology, or domains" as a shortfall feedback loop, labeled single-source/conflicting claims held "until reviewed", and a failure-handling section with per-error recovery steps. Batch mode isolates failures per query with errors kept in each result envelope, so the batch-operation cap does not apply.

5 / 5

Progressive Disclosure

Sections are well-organized with clear headers and the script bundle is real (scripts/research_lookup.py and scripts/manuscript_packet.py exist and the documented invocation path resolves to them), but at ~336 lines everything lives inline in SKILL.md with no reference files at all — backend compatibility minutiae, packet artifact specs, and citation instructions are content that could be split into one-level-deep reference docs. It is above the 2 anchor because the content is well-sectioned workflow guidance rather than an unstructured API dump, but below 4 because a document this long should offload detail rather than keep it all on the front page.

3 / 5

Total

17

/

20

Passed

Description

83%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.

A strong description: explicit third-person what and when clauses with an enumerated trigger list and concrete backend routing. The main gaps are a slightly implementation-flavored routing sentence and a few missing common trigger synonyms.

DimensionReasoningScore

Specificity

Concrete actions are named — "Compile current scholarly evidence", "gather literature, references, background evidence, competing findings, or a manuscript research packet", plus backend-specific routing (Parallel Search/Extract/Research). It falls short of a 5 because the deliverable artifacts (evidence matrix, claim-source map, references.bib) and the verification action are only implied via tool names rather than stated as capability outcomes, and the routing sentence reads as implementation detail rather than capability coverage.

4 / 5

Completeness

Both what and when are explicit: "Compile current scholarly evidence for a scientific manuscript or research brief" answers what, and "Use when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet" gives concrete trigger phrases. The neighboring 4 anchor (when 'could be more explicit or specific') fits worse since the trigger list is enumerated and specific.

5 / 5

Trigger Term Quality

Natural user phrasing is well covered: "gather literature", "references", "background evidence", "competing findings", "scientific manuscript or research brief", "research packet". It does not reach 5 because common variations like "citations", "find papers", "literature review", or "evidence for my claim" are absent, and "competing findings" is a less natural phrase than "contradicting evidence".

4 / 5

Distinctiveness Conflict Risk

The manuscript-evidence niche with the "explicitly asks" trigger guard keeps it from firing on casual questions, and it distinguishes itself from generic web search. Minor overlap remains with closely related skills (literature-review, deep-research, general search) that the description does not itself disambiguate; a 5 would require the niche triggers to leave essentially no overlap, which the shared terms 'literature' and 'research' don't quite achieve.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
K-Dense-AI/claude-scientific-writer
Reviewed

Table of Contents

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