groq-performance-tuning

Optimize Groq API performance with model selection, caching, streaming, and parallel requests. Use when experiencing slow responses, implementing caching strategies, or optimizing request throughput for Groq integrations. Trigger with phrases like "groq performance", "optimize groq", "groq latency", "groq caching", "groq slow", "groq speed".

Quality

86%

Does it follow best practices?

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Securityby

Passed

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Quality

Content

72%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 content is highly actionable and well-structured with real executable code and a clean progressive-disclosure split across two verified reference files. It is slightly verbose in places and lacks an explicit feedback loop for its batch/rate-limit operations, capping workflow clarity.

Suggestions

Tighten the Overview's closing sentence and de-duplicate the lever descriptions that reappear in the Output section to improve conciseness.

Add an explicit measure-then-revert checkpoint to the parallelize/bulk lever (e.g., 'if throughput drops or 429s persist, reduce concurrency and re-measure') to close the batch-operation feedback loop.

Replace any safe-looking ceiling guidance with a one-line 'set max_tokens to observed output size' rule in the body itself rather than only in references.

Dimension	Reasoning	Score
Conciseness	The body mostly assumes Claude's competence (no "what is Groq/LPU" exposition) and uses terse tables and bullets, but a few sentences such as "determines whether your application fully exploits that speed" and restatement between Instructions and Output could be tightened.	2 / 3
Actionability	It provides copy-paste-ready TypeScript with concrete model IDs, `temperature: 0`, and explicit `max_tokens` values plus a decision matrix with specific numbers, offloading full functions to executable references.	3 / 3
Workflow Clarity	The six levers are ordered with a benchmark checkpoint, but batch/parallel and rate-limit operations lack an explicit measure-revert feedback loop, and the rubric caps batch-operation workflows at 2 when validation is implicit.	2 / 3
Progressive Disclosure	SKILL.md is a clear overview pointing to two confirmed one-level-deep references (implementation.md, examples.md), each signaled multiple times with distinct purpose and no nested indirection.	3 / 3
	Total	10 / 12 Passed

Description

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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, well-triggered, and complete, naming four concrete optimization levers alongside explicit use-when guidance and natural trigger phrases. It is clearly distinct from sibling skills and avoids vague language.

Dimension	Reasoning	Score
Specificity	"Optimize Groq API performance with model selection, caching, streaming, and parallel requests" lists four concrete, distinct capabilities rather than vague actions, matching the multi-action anchor.	3 / 3
Completeness	It explicitly states what the skill does and includes a clear "Use when experiencing slow responses, implementing caching strategies, or optimizing request throughput" clause, answering both what and when.	3 / 3
Trigger Term Quality	Trigger phrases like "groq performance", "groq slow", and "groq speed" are natural terms a user would actually say, giving good coverage rather than jargon.	3 / 3
Distinctiveness Conflict Risk	Every trigger and capability is Groq-scoped, carving a clear niche that is unlikely to fire for non-Groq or cost-tuning 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
Path: plugins/saas-packs/groq-pack/skills/groq-performance-tuning/SKILL.md
Commit: 4c47e33

Reviewed: about 23 hours ago

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