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web-search-tavily

AI-powered web search, crawling, extraction, and deep research

47

Quality

59%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/research-tools/capabilities/web-search-tavily/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

38%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.

The body is a self-contained API catalog with real curl commands and Tavily-specific parameter detail, but it inlines ~150 lines of reference material that belongs in separate files, repeats parameter descriptions verbatim, and ships two malformed curl examples. Restructuring into an overview plus reference files and fixing the broken examples would address the weakest dimensions.

Suggestions

Move the per-endpoint parameter reference into a references/ file (e.g. references/endpoints.md) and keep SKILL.md as a concise overview with one working example per capability and clearly signaled one-level-deep links.

Fix the malformed curl examples for Tavily Search and Tavily Crawl so all parameters are inside the -d JSON body (e.g. -d '{"api":"tavily","path":"/search","body":{"query":"...","search_depth":"advanced","include_answer":true}}').

Deduplicate the chunks_per_source and credit-cost text repeated across Search/Extract/Crawl, and spell out the research workflow as an explicit sequence: create task → save request_id → poll Get Research Task Status until complete.

DimensionReasoningScore

Conciseness

The ~150-line parameter dump is noticeably verbose: the chunks_per_source description is repeated nearly verbatim in the Search, Extract, and Crawl sections, and credit-cost prose pads multiple parameters. This goes beyond the minor trimming of anchor 3 into repeated, padded sections.

2 / 5

Actionability

Setup and the Extract/Map/Research curl examples are concrete and executable, but the Tavily Search example (lines 62-66) and Tavily Crawl example (lines 164-167) have malformed JSON — parameters appear outside the -d request body string — leaving key details broken. This is more than the minor gaps of anchor 4.

3 / 5

Workflow Clarity

Capabilities are catalogued per-endpoint but never sequenced: the create-research-task → poll-status-by-request_id flow is implied rather than stated, and there is no error-handling or verification guidance for batch crawl/map operations. Anchor 3 (steps/sequence present but checkpoints missing) fits; not 4 since no workflow is actually laid out.

3 / 5

Progressive Disclosure

No bundle files exist and the entire API parameter reference is inlined in SKILL.md, which clearly belongs in separate reference files; sections exist but the bulk reference is not split or offloaded, matching anchor 2.

2 / 5

Total

10

/

20

Passed

Description

62%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 terse, domain-focused description that names four concrete capabilities with natural trigger keywords, but it omits any "when to use" guidance and leans on the "AI-powered" buzzword. Adding an explicit trigger clause and a distinguishing detail would lift it substantially.

Suggestions

Add a "Use when..." clause, e.g. "Use when the user asks to search the web, scrape or extract content from URLs, crawl a documentation site, or produce a sourced research report on a topic."

Drop the "AI-powered" buzzword and replace it with a concrete distinguishing detail (e.g. the Tavily API / single-request deep research reports) to reduce overlap with other search and research skills.

Include common synonyms users actually say — "scrape", "fetch/read this page", "find sources" — to improve trigger term coverage.

DimensionReasoningScore

Specificity

"web search, crawling, extraction, and deep research" lists several concrete actions with minor gaps, matching the anchor for several specific actions; it is not 5 because the actions are named without any detail, and "AI-powered" is buzzword padding.

4 / 5

Completeness

The description clearly answers "what" (search, crawl, extract, research) but contains no "Use when..." clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

"web search", "crawling", and "deep research" are phrases users naturally say when needing this skill, giving good keyword coverage; it falls short of 5 because common synonyms like "scrape", "fetch this page/URL", or "find sources" are absent.

4 / 5

Distinctiveness Conflict Risk

"deep research" and generic search wording overlap with other search/research skills, so it is somewhat specific but could still conflict with closely related skills; it is not 4 because nothing marks out a clear niche or distinct trigger.

3 / 5

Total

14

/

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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