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literature-review

Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

57

Quality

67%

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SecuritybySnyk

Low

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tessl review fix ./configs/microservice/bff-service/configs/agent-skills/claude-science/literature-review/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

A dense, expert-level instruction skill with strong actionability (exact commands, env vars, formats, and a lint-and-save finishing step) and a clearly ordered workflow with real verification checkpoints. Its weaknesses are repetition of the same guidance across sections, missing helper usage examples, no error-recovery paths, and a referenced kernel.py that is not present in the bundle.

Suggestions

State the kernel.py helper signatures (or one example call each) once — e.g. `search_openalex(query) -> records` — instead of repeating the bare helper-name list in three separate sections.

Merge the three overlapping prose-quality sections ("Synthesis is comparison", "Making the prose carry its weight", "Write prose, not a bulleted bibliography") into one, keeping the strongest examples from each.

Add brief failure-handling guidance — what to do when a DOI fails verification, when OPENALEX_API_KEY is absent, or when a sweep returns nothing — and ensure kernel.py ships with the bundle so the Setup reference resolves.

DimensionReasoningScore

Conciseness

The body assumes Claude's competence — no explanations of what a DOI or literature review is — but repeats itself: the kernel.py helper list appears three times ("verify_dois, crossref_lookup, search_openalex, expand_citations, extract_dois, style_pass" in Setup, again in the citation-format section, and again in Style pass), and the prose-not-bullets principle is restated across "Synthesis is comparison", "Making the prose carry its weight", and "Write prose, not a bulleted bibliography". Not 2: the padding is repetition of genuinely useful craft guidance, not explanation of known concepts; not 4 because a tightening pass would remove several redundant restatements.

3 / 5

Actionability

Concrete, executable guidance throughout: the exact `exec(open("<this skill's directory>/kernel.py").read())` load line, named env vars (`OPENALEX_API_KEY`, `HOST_USER_EMAIL`) with the signup URL, named helper functions, the exact citation markdown format `[Author Year](https://doi.org/10.xxxx/xxxxxx)` with the `%28`/`%29` URL-encoding rule, and the one-shot `style_pass(draft)` procedure. Not 5: no helper signatures or a single example call (e.g. what `search_openalex` takes or returns), so first use requires inspecting kernel.py.

4 / 5

Workflow Clarity

Sections are ordered as a real workflow — load helpers → read the request type → retrieval sweep → backward/forward citation expansion via `expand_citations(doi)` → retraction check → synthesis → style pass → save — with verification checkpoints ("Verification is something that happens in your tool trace", the update-to retraction check, and the explicit style-pass-then-save step). Not 5: no error-recovery guidance (failed DOI verification, missing OPENALEX_API_KEY, empty search results), so feedback loops are absent even though the sequence and checkpoints are clear.

4 / 5

Progressive Disclosure

The body has clear, well-named sections and exactly one external reference (`kernel.py`), which is clearly signaled in Setup. However, the bundle contains no kernel.py (and no references/, scripts/, or assets/ directories), so the skill's single referenced file cannot be verified to exist, and helper API details are inlined in the body rather than disclosed from a reference. Not 4: a referenced-but-absent core file is more than a minor organization gap for an agent following the skill.

3 / 5

Total

14

/

20

Passed

Description

71%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 specific, third-person description with strong concrete action verbs and good domain keywords, including a naturally quoted user query. Its main weakness is the absence of an explicit "Use when..." trigger clause, which caps completeness and leaves invocation guidance implicit.

Suggestions

Add an explicit trigger clause, e.g. "Use when asked to find papers, verify citations or DOIs, check for retractions, or write a literature review or evidence synthesis."

Include common natural synonyms users would say — "papers", "references", "literature review", "search the literature" — alongside "scientific literature".

State the boundary versus general web research briefly (e.g. 'for scientific/academic sources specifically') to reduce overlap with generic research skills.

DimensionReasoningScore

Specificity

"Find, verify, and synthesize scientific literature" plus "grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength" names multiple specific concrete actions covering retrieval, verification, synthesis, and calibration. Not 4: coverage is comprehensive across the skill's capabilities, not just several actions with gaps.

5 / 5

Completeness

The 'what' is clear and detailed, but there is no "Use when..." clause or equivalent explicit trigger guidance; the quoted query "from 'what's the seminal paper for X' through full multi-source reviews" describes scope of requests, not when to invoke the skill. Per guideline, missing trigger guidance caps completeness at 3; not 2 because the 'what' half is explicit and the 'when' is weakly implied by the request-range phrasing.

3 / 5

Trigger Term Quality

Good natural keywords — "scientific literature", "seminal paper", "citations", "retractions", "reviews", and the quoted user query "what's the seminal paper for X". Not 5: common variations users would actually say are missing ("papers", "references", "find papers", "literature review", "search the literature").

4 / 5

Distinctiveness Conflict Risk

A clear niche — citation verification, retraction handling, evidence-calibrated synthesis with named services — distinguishes it from generic skills. Not 5: "find and synthesize" overlaps with general research/deep-research skills, and without explicit trigger phrasing the boundary is implicit.

4 / 5

Total

16

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

14

/

16

Passed

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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