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survey-generator

Compile a structured literature survey on any AI/ML topic. Agent curates a research bundle (taxonomy + sections + bibliography of real papers) from a public anchor resource, then a chosen LLM generates the survey artifact. Output target is a wiki page (markdown), not a one-off HTML — survey lands in `<wiki>/derived/surveys/<slug>.md` with full bibliography rows in `sources.md`. Provider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom OpenAI-compat). Use when the user asks for a "survey", "literature review", "lit review", or "deep dive" on a technical topic.

Quality

81%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 well-structured, action-dense skill body with concrete commands, a complete bundle schema, and a clearly sequenced workflow. The main defects are navigation and completeness of the bundle: two referenced files are missing, two documented flags are absent from the CLI synopsis, and the workflow lacks an explicit validation checkpoint on the generated survey.

Suggestions

Fix the dangling references: either add templates/research_bundle.template.json and the provider-configuration reference at the linked path, or remove the links and inline the minimal needed detail — as written, both navigation points dead-end.

Add --bibliography-size N and --section-count N to the build-survey.js CLI synopsis so the documented Inputs table matches the executable commands.

Add an explicit validation checkpoint in Step 4 before upserting: verify every [^src-bib-<slug>] citation in the generated survey resolves to a bibliography key and all 6-10 sections are present; if not, tighten sections[].guidance and rerun.

DimensionReasoningScore

Conciseness

The body is dense and table-driven — Inputs table, JSON bundle schema, single-command CLI blocks, output tree — with no explanation of concepts Claude already knows. It misses 5 mainly because the 'Diff vs dair-academy version' comparison table is provenance commentary rather than instruction, adding tokens that do not earn their place during execution.

4 / 5

Actionability

Mostly executable guidance: the full bundle JSON schema with required keys, the MCP call with concrete args, and copy-paste 'node $SKILL_ROOT/scripts/build-survey.js --bundle ... --wiki ... [--provider ...] [--model ...]' commands. Gaps keep it below 5: '--bibliography-size' and '--section-count' appear in the Inputs table but never in the CLI synopsis, and two referenced files ('templates/research_bundle.template.json', '../../references/provider-configuration.md') do not exist in the bundle.

4 / 5

Workflow Clarity

Steps 1-4 are clearly sequenced (read anchor → build bundle → run generator → iterate) with hard rules as constraints and an explicit rerun feedback loop ('If prose is thin: tighten sections[].guidance and rerun'). Not 5 because there is no validation checkpoint on the generated output — nothing instructs checking that citations resolve to bibliography keys or that all sections were produced before upserting.

4 / 5

Progressive Disclosure

The body itself is well sectioned with clear headers, but scored against the actual bundle: the only bundle file is scripts/build-survey.js, while 'templates/research_bundle.template.json' and the link '[provider configuration](../../references/provider-configuration.md)' are dangling — those referenced paths do not exist, so navigation to the promised detail fails. This matches the 'some structure but references not properly backed' level rather than 4, where references would resolve and be well signaled.

3 / 5

Total

15

/

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: third-person voice, explicit what-and-when with concrete trigger phrases, and good natural-language keyword coverage with synonyms. The main weakness is that file-path and provider enumeration detail dilutes the capability statement, and a couple of natural trigger variants are missing.

DimensionReasoningScore

Specificity

Quotes list several concrete actions — 'Compile a structured literature survey', 'curates a research bundle (taxonomy + sections + bibliography of real papers)', 'generates the survey artifact', 'lands in <wiki>/derived/surveys/<slug>.md' — matching the 'several specific actions; minor gaps' anchor. It falls short of 5 because the file-path and provider-list detail is implementation context rather than additional capability actions, and iteration/verification actions are absent.

4 / 5

Completeness

Both what and when are answered explicitly and concretely: the what ('Compile a structured literature survey... curates a research bundle... generates the survey artifact') is specific, and the when is an explicit trigger clause ('Use when the user asks for a "survey", "literature review", "lit review", or "deep dive" on a technical topic'). This matches the top anchor exactly.

5 / 5

Trigger Term Quality

Includes natural phrases users would say — '"survey"', '"literature review"', '"lit review"', '"deep dive" on a technical topic' — giving good keyword coverage with synonyms. Not 5 because common variations like 'state of the field', 'map of the field', or 'reading list' are missing; not 3 because multiple natural synonyms are present rather than just one or two generic keywords.

4 / 5

Distinctiveness Conflict Risk

The 'literature survey / lit review on a technical topic' niche is mostly distinct with clear triggers, fitting the 'mostly distinct; minor overlap risk' anchor. Not 5 because the generic trigger 'deep dive' could also match general research or deep-research skills; not 3 because the core triggers are far more specific than the overlapping examples at that level.

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

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository

rohitg00/pro-workflow

Path

skills/survey-generator/SKILL.md

Reviewed

Table of Contents

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