firecrawl-load-scale
Load test and scale Firecrawl scraping pipelines with concurrency control and batching. Use when testing scraping throughput, planning capacity for large crawl jobs, or optimizing concurrent scrape performance. Trigger with phrases like "firecrawl load test", "firecrawl scale", "firecrawl throughput", "firecrawl capacity", "firecrawl concurrent".
84
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
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 an excellent skill description that clearly defines its niche at the intersection of Firecrawl and performance/load testing. It provides concrete capabilities, explicit 'Use when' guidance, and a comprehensive list of trigger phrases. The description is concise, uses third-person voice, and would be easily distinguishable from other skills in a large collection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple concrete actions: load testing, scaling pipelines, concurrency control, and batching. These are specific, actionable capabilities rather than vague language. | 3 / 3 |
Completeness | Clearly answers both 'what' (load test and scale Firecrawl scraping pipelines with concurrency control and batching) and 'when' (explicit 'Use when' clause covering testing throughput, planning capacity, optimizing performance, plus explicit trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes a rich set of natural trigger terms: 'firecrawl load test', 'firecrawl scale', 'firecrawl throughput', 'firecrawl capacity', 'firecrawl concurrent', plus contextual phrases like 'scraping throughput' and 'large crawl jobs'. These are terms users would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of 'Firecrawl' + 'load test/scale/throughput'. This is a clear niche that would not overlap with general scraping skills or general load testing 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.
This is a solid, actionable skill with executable code examples covering the full load testing and scaling workflow for Firecrawl. Its main strengths are concrete, copy-paste-ready TypeScript and a useful rate limits reference table. Weaknesses include missing validation checkpoints within the workflow (important for operations that consume credits/hit rate limits) and a somewhat monolithic structure that could benefit from splitting detailed implementations into separate files.
Suggestions
Add explicit validation checkpoints within the workflow, e.g., 'Verify your plan tier and current usage before running load tests' and 'Check error rate after Step 1 before scaling up concurrency in subsequent steps.'
Consider splitting the detailed code implementations (Steps 3-5) into separate referenced files to keep SKILL.md as a concise overview with quick-start examples.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The rate limits table and error handling table are valuable additions that earn their tokens. However, the capacity planning function is somewhat verbose for what it does (basic arithmetic), and some code blocks could be tightened. The overview paragraph is slightly redundant given the title and context. | 2 / 3 |
Actionability | All code examples are fully executable TypeScript with proper imports, concrete function signatures, and real API calls. The examples cover the full spectrum from baseline measurement to batch scraping, queue management, async crawls, and capacity planning—all copy-paste ready. | 3 / 3 |
Workflow Clarity | The steps are clearly sequenced from baseline measurement through scaling, but there are no explicit validation checkpoints or feedback loops. For load testing (which can be destructive to rate limits/credits), there should be validation steps like 'verify your plan limits before running' or 'check error rate before increasing concurrency.' The error handling table helps but is separate from the workflow. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and a logical progression, but at ~180 lines of code-heavy content, some sections (like the capacity planning function or the parallel crawls implementation) could be split into referenced files. The reference to 'firecrawl-reliability-patterns' is good, but 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 | |
- Commit
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- Reviewed
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