langchain-cost-tuning
Optimize LangChain API costs with token tracking, model tiering, caching, prompt compression, and budget enforcement. Trigger: "langchain cost", "langchain tokens", "reduce langchain cost", "langchain billing", "langchain budget", "token optimization".
67
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
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.
This is a strong skill description that clearly communicates specific capabilities (token tracking, model tiering, caching, prompt compression, budget enforcement) within a well-defined niche (LangChain API cost optimization). The explicit trigger terms cover natural user language variations effectively, and the description is concise without unnecessary fluff.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: token tracking, model tiering, caching, prompt compression, and budget enforcement. These are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (optimize LangChain API costs with specific techniques) and 'when' (explicit trigger terms listed with a 'Trigger:' clause that serves the same function as 'Use when'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'langchain cost', 'langchain tokens', 'reduce langchain cost', 'langchain billing', 'langchain budget', 'token optimization'. Good coverage of variations a user might naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining LangChain with cost optimization. The trigger terms are all LangChain-specific, making it very unlikely to conflict with general cost optimization or general LangChain skills. | 3 / 3 |
Total | 12 / 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.
The skill provides highly actionable, executable code examples across five distinct cost optimization strategies, which is its primary strength. However, it's somewhat verbose for a skill file—the pricing table with specific dates, inline explanations, and five fully expanded strategies make it long without clear sequencing or validation checkpoints. The content would benefit from being split across files with SKILL.md serving as an overview, and from adding verification steps to confirm optimizations are working.
Suggestions
Add a verification workflow: after implementing each strategy, include a concrete step to measure before/after costs (e.g., 'Run tracker.report() before and after enabling caching to confirm savings').
Move detailed code examples for each strategy into separate referenced files (e.g., CACHING.md, TIERING.md) and keep SKILL.md as a concise overview with quick-start snippets.
Remove or relocate the 2026 pricing table to a separate PRICING.md file since it's time-sensitive and will become stale, or add a note about verifying current prices.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The pricing table with specific 2026 dates is a liability, and some comments in code are unnecessary (e.g., explaining what caching does). The prompt compression example's 'before' verbose prompt is illustrative but adds bulk. Overall mostly efficient but could be tightened—the error handling table and checklist table add value but the overall document is long for what it teaches. | 2 / 3 |
Actionability | All five strategies include fully executable, copy-paste-ready code examples in TypeScript and Python with proper imports, concrete class implementations, and realistic usage patterns. The code is complete and specific, not pseudocode. | 3 / 3 |
Workflow Clarity | The strategies are presented as independent modules rather than a sequenced workflow. There's no guidance on which order to implement them, no validation steps (e.g., verify cache is working, confirm cost tracking accuracy), and no feedback loops for verifying that optimizations actually reduced costs. The checklist helps but lacks explicit verification checkpoints. | 2 / 3 |
Progressive Disclosure | The content is a monolithic single file with all five strategies fully inline. Given the length (~200+ lines of code), the caching, tiering, and budget enforcement sections could be split into separate reference files. The 'Resources' and 'Next Steps' sections provide some external navigation but the main body is a wall of content that would benefit from better structuring across files. | 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 | |
- Commit
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- Reviewed
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