groq-cost-tuning
Optimize Groq costs through model routing, token management, and usage monitoring. Use when analyzing Groq billing, reducing API costs, or implementing usage monitoring and budget alerts. Trigger with phrases like "groq cost", "groq billing", "reduce groq costs", "groq pricing", "groq expensive", "groq budget".
64
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/groq-pack/skills/groq-cost-tuning/SKILL.mdQuality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-structured skill description that clearly identifies its niche (Groq cost optimization), provides explicit trigger guidance with natural user phrases, and answers both what and when. The main weakness is that the capability descriptions could be more concrete — listing specific actions rather than broad categories like 'model routing' and 'token management' would strengthen specificity.
Suggestions
Make capabilities more concrete by listing specific actions, e.g., 'Compare model pricing tiers, estimate per-request costs, set budget thresholds, analyze token usage patterns, recommend cheaper model alternatives'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Groq costs) and some actions (model routing, token management, usage monitoring), but these are somewhat high-level categories rather than multiple concrete, specific actions like 'set budget alerts, analyze token usage per endpoint, compare model pricing tiers'. | 2 / 3 |
Completeness | Clearly answers both 'what' (optimize Groq costs through model routing, token management, usage monitoring) and 'when' (explicit 'Use when' clause with specific scenarios plus a 'Trigger with phrases' section listing concrete trigger terms). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would actually say: 'groq cost', 'groq billing', 'reduce groq costs', 'groq pricing', 'groq expensive', 'groq budget'. These are realistic phrases a user would type when seeking help with Groq cost optimization. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — focuses specifically on Groq API cost optimization, which is a clear niche. The Groq-specific trigger terms make it very unlikely to conflict with general cost optimization or other API provider skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with executable TypeScript code covering model routing, token minimization, batching, caching, and usage tracking. Its main weaknesses are the lack of validation checkpoints (e.g., verifying 8B quality is acceptable before routing all traffic there) and the monolithic structure that could benefit from splitting detailed implementations into referenced files. The pricing table with approximate values introduces maintenance burden and time-sensitivity risk.
Suggestions
Add a validation step for model routing quality—e.g., 'Test 50 samples on both 8B and 70B, compare accuracy before committing to routing rules' to create a feedback loop.
Extract the detailed code implementations (caching, batching, tracking) into separate referenced files to improve progressive disclosure and reduce the main skill's token footprint.
Add a note that pricing values are approximate and may change, or move the pricing table to a separate maintainable reference file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with good code examples, but includes some unnecessary verbosity—the pricing table with approximate values that may change, inline cost math comments that are somewhat redundant, and the cost comparison table at the end adds bulk. The code examples themselves are reasonably lean but could be tighter. | 2 / 3 |
Actionability | All code examples are fully executable TypeScript with proper imports, typed interfaces, and complete function implementations. The routing table, caching, batching, and tracking code are all copy-paste ready with concrete model names and pricing. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced, but there are no validation checkpoints—no guidance on verifying that model routing is actually saving costs, no way to confirm cache hit rates, and no feedback loop for checking if the 8B model quality is sufficient for a given use case before committing to it at scale. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections, but it's quite long (~180 lines of substantive content) and could benefit from splitting the detailed code examples into separate files. The reference to `groq-reference-architecture` at the end is good, but the inline code for caching, batching, and tracking could be externalized. No bundle files exist to support progressive disclosure. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 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 | 9 / 11 Passed | |
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