exa-data-handling

Implement Exa search result processing, content extraction, caching, and RAG context management. Use when handling search results, implementing caching, building citation pipelines, or managing content payloads for LLM context windows. Trigger with phrases like "exa data", "exa results processing", "exa cache", "exa RAG context", "exa content extraction".

Quality

—

Does it follow best practices?

Impact

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No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Quality

Content

65%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is highly actionable with executable TypeScript throughout and clear step sequencing, but it is slightly held back by a redundant composite example, implicit-only validation checkpoints, and an all-inline structure with no progressive disclosure into reference files.

Suggestions

Trim or collapse the 'RAG-Optimized Search Pipeline' example since it recombines code already shown in Steps 2-4, or replace it with a genuinely new integration scenario.

Add an explicit validation checkpoint inside the RAG pipeline (e.g., verify tokenCount fits the budget and dropped count is acceptable before returning context) rather than relying on the after-the-fact error table.

Move the detailed per-tier code or the error-handling reference into a references/ file and link to it from SKILL.md so the overview stays lean and material is split one level deep.

Dimension	Reasoning	Score
Conciseness	The body is mostly lean code with no concept re-explanation, but the 'Examples: RAG-Optimized Search Pipeline' section recombines cachedSearch, deduplicateResults, processForRAG, and fitToTokenBudget already shown in Steps 2-4, so not every token earns its place.	2 / 3
Actionability	Each step provides fully executable exa-js TypeScript with real SDK calls (searchAndContents, summary/highlights options, LRU caching), specific parameters, and copy-paste-ready snippets.	3 / 3
Workflow Clarity	Steps 1-5 are clearly sequenced and an error-handling table exists, but validation checkpoints are only implicit (an after-the-fact table) rather than woven into the workflow as explicit validate-then-proceed gates.	2 / 3
Progressive Disclosure	Sections are well organized (Overview, Prerequisites, Steps, Error Handling, Examples, Resources, Next Steps), but ~220 lines live entirely inline in SKILL.md with no bundle reference files to split deeper material into, so content that could be separate stays inline.	2 / 3
	Total	9 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, complete, and distinctive, explicitly covering what the skill does, when to use it, and concrete trigger phrases. It avoids vague fluff and uses the active base-verb form consistent with the strong reference examples.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions — 'search result processing, content extraction, caching, and RAG context management' — matching the anchor that lists several specific capabilities rather than a vague domain label.	3 / 3
Completeness	It states the what ('Implement Exa search result processing...') and an explicit when ('Use when handling search results, implementing caching...') plus concrete trigger phrases, clearly answering both what and when.	3 / 3
Trigger Term Quality	Trigger phrases 'exa data', 'exa results processing', 'exa cache', 'exa RAG context', and 'exa content extraction' give good coverage of the natural terms a user would say across the skill's scope.	3 / 3
Distinctiveness Conflict Risk	The Exa-specific niche and branded 'exa ...' triggers make it clearly distinguishable and unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 02d6341

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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