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

90%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

—

The risk profile of this skill

Quality

Content

80%Weight 40%Scale 1-3

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

The body is concise and highly actionable with executable TypeScript throughout, but it presents a long monolithic document with no progressive disclosure via separate files and no explicit validation checkpoints in its workflows. Splitting reference material out and adding validation feedback loops would raise the two lower dimensions.

Suggestions

Add explicit validation checkpoints to the RAG pipeline workflow (e.g., verify cache hits, confirm token budget was respected before returning context, retry/trim on overflow) to turn the sequenced steps into a feedback-loop workflow.

Move the detailed per-tier code examples and the full RAG pipeline into a referenced file (e.g., references/rag-pipeline.md) and keep SKILL.md as a concise overview pointing to it, improving progressive disclosure.

Confirm the cross-skill "Next Steps" pointers (exa-rate-limits, exa-cost-tuning) resolve to real sibling skills, since there are currently no bundle files to verify them against.

Dimension	Reasoning	Score
Conciseness	The body is code-first with terse prose (Overview, Prerequisites, inline tier comments) and does not explain concepts Claude already knows (e.g., what caching or RAG is). It matches the lean, efficient top anchor rather than the padded level-2 example.	3 / 3
Actionability	Each step provides fully executable TypeScript (cachedSearch, processForRAG, fitToTokenBudget, deduplicateResults) plus a complete RAG pipeline example, all copy-paste ready. This matches the anchor for executable code with specific examples, not the pseudocode level-2 anchor.	3 / 3
Workflow Clarity	Steps 1-5 and the RAG example pipeline are clearly sequenced, but there are no explicit validation checkpoints or fix-retry feedback loops within the workflow (the Error Handling table is a troubleshooting reference, not embedded validation). This matches the level-2 anchor of listed steps with missing checkpoints, and does not reach level 3 which requires explicit validation steps.	2 / 3
Progressive Disclosure	Sections are well organized (Overview, Prerequisites, Instructions, Error Handling, Examples, Resources, Next Steps) with no nested references, but everything lives inline in a ~220-line monolithic file with no file-level disclosure. It does not reach level 3 because detailed reference material is not split into separate files, and the under-50-line simple-skill exemption does not apply.	2 / 3
	Total	10 / 12 Passed

Description

100%Weight 40%Scale 1-3

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: it names concrete actions, provides an explicit "Use when" trigger with multiple natural phrases, and is clearly scoped to Exa. No changes needed.

Dimension	Reasoning	Score
Specificity	"Implement Exa search result processing, content extraction, caching, and RAG context management" lists multiple concrete actions (processing, extraction, caching, RAG management), matching the anchor for several specific actions. It is not the level below, which only names a domain and partial actions.	3 / 3
Completeness	It explicitly answers what ("Implement Exa search result processing...") and when ("Use when handling search results, implementing caching...") with an explicit "Use when" clause and trigger phrases, matching the top anchor. It is not level 2 because the trigger guidance is explicit, not merely implied.	3 / 3
Trigger Term Quality	Trigger phrases "exa data", "exa results processing", "exa cache", "exa RAG context", "exa content extraction" give good coverage of natural terms a user working with Exa would say. It exceeds the level-2 anchor (a single relevant keyword) by covering multiple variations.	3 / 3
Distinctiveness Conflict Risk	The skill is tightly scoped to Exa with Exa-specific triggers ("exa cache", "exa RAG context"), giving it a clear niche unlikely to conflict with other skills. It is not level 2 because the scope is far more specific than "Works with document files".	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
Path: plugins/saas-packs/exa-pack/skills/exa-data-handling/SKILL.md
Commit: 0540a62

Reviewed: 44 minutes ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.