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exa-search

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

83

7.00x
Quality

85%

Does it follow best practices?

Impact

98%

7.00x

Average score across 2 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%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 clean, highly actionable tool reference with concrete examples and parameter tables for every tool. The main weakness is mild redundancy between Core Tools and Usage Patterns, and no progressive offloading of detail into reference files.

Suggestions

Trim the 'Usage Patterns' section to show only combinations not already demonstrated in Core Tools (e.g., the company due-diligence pairing), removing duplicated single-tool examples.

Add brief guidance for the async deep-research flow on check timing and what to do when deep_researcher_check reports failure or an incomplete state.

Consider moving the per-tool parameter tables into a reference file (e.g. references/tools.md) so SKILL.md stays a lean overview with one-level-deep navigation.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence, but the 'Usage Patterns' section repeats examples already shown verbatim in the Core Tools sections, adding tokens without new information.

4 / 5

Actionability

Every tool is shown with a concrete, copy-paste-ready call signature and a full parameter table with types and defaults, covering the common cases.

5 / 5

Workflow Clarity

The async deep-research sequence (start → check by researchId) is clearly shown, and operations are read-only so the destructive-cap does not apply; minor gaps are no guidance on check timing or failure handling.

4 / 5

Progressive Disclosure

Well-organized single-file structure with clearly labeled sections (When to Activate, MCP Requirement, Core Tools, Tips), but at ~165 lines with all detail inline there is no one-level-deep reference offloading.

4 / 5

Total

17

/

20

Passed

Description

88%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, well-structured description that clearly states capabilities and triggers in third person with concrete actions. Trigger terms could be slightly more natural and the niche more sharply separated from sibling research skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'web search, code examples, company intel, people lookup, or AI-powered deep research' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what ('Neural search via Exa MCP for web, code, and company research') and when ('Use when the user needs...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Good natural keywords ('web search', 'code examples'), but 'company intel' and 'people lookup' read as skill jargon rather than phrases users naturally say; a few synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

The Exa MCP niche is specific and distinct, but search is a crowded domain and the skill itself lists overlapping related skills, leaving minor conflict risk.

4 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
affaan-m/ECC
Reviewed

Table of Contents

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