firecrawl-reference-architecture
Implement Firecrawl reference architecture with scrape/crawl/map/extract pipelines. Use when designing new Firecrawl integrations, reviewing project structure, or building content ingestion pipelines for AI/RAG applications. Trigger with phrases like "firecrawl architecture", "firecrawl project structure", "firecrawl pipeline", "firecrawl RAG", "firecrawl knowledge base".
84
82%
Does it follow best practices?
Impact
Pending
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 a strong skill description that clearly identifies its niche (Firecrawl reference architecture), lists specific capabilities (scrape/crawl/map/extract pipelines), provides explicit 'Use when' guidance, and includes natural 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 specific concrete actions: 'scrape/crawl/map/extract pipelines', 'designing new Firecrawl integrations', 'reviewing project structure', 'building content ingestion pipelines for AI/RAG applications'. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (implement Firecrawl reference architecture with scrape/crawl/map/extract pipelines) and 'when' (designing new integrations, reviewing project structure, building content ingestion pipelines) with explicit trigger phrases. | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases: 'firecrawl architecture', 'firecrawl project structure', 'firecrawl pipeline', 'firecrawl RAG', 'firecrawl knowledge base'. These are terms users would naturally use when seeking this skill. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific 'Firecrawl' domain focus and the combination of scrape/crawl/map/extract pipelines with RAG applications. The trigger terms are all Firecrawl-specific, making conflicts with other skills very unlikely. | 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 reference architecture with complete, executable TypeScript code covering all four Firecrawl endpoints. Its main weaknesses are the lack of explicit validation/error-recovery steps integrated into the workflows and the monolithic inline presentation of all implementation code. The error handling table is useful but disconnected from the step-by-step flow.
Suggestions
Integrate validation checkpoints directly into the workflow steps (e.g., 'Verify crawl.success before processing', 'Check scrape response status and retry on failure') rather than listing errors in a separate table.
Consider splitting the full implementation code into referenced files (e.g., 'See src/pipeline/processor.ts for full implementation') and keeping only the key patterns and API usage inline in SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with executable code, but the architecture diagram and some inline comments add bulk. The content is substantial (~180 lines) and could be tightened—e.g., the error handling table and some wrapper functions are straightforward patterns Claude could derive. However, it doesn't over-explain basic concepts. | 2 / 3 |
Actionability | Fully executable TypeScript code throughout with concrete function signatures, real API calls, and copy-paste ready implementations. Each step provides complete, runnable code with specific Firecrawl SDK methods, options, and processing logic. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced (service layer → processing → intelligent scrape → crawl+store), and the map+scrape pipeline has a logical 1-2-3 flow with deduplication. However, there are no explicit validation checkpoints or error recovery feedback loops—the error handling table lists issues but doesn't integrate validation into the workflow steps themselves. | 2 / 3 |
Progressive Disclosure | The content has clear section headers and a resources section linking to external docs, but the bulk of the implementation is inline rather than split into referenced files. For a skill this long, the full processing pipeline and storage code could be referenced rather than fully inlined. The 'Next Steps' reference to firecrawl-multi-env-setup is good but minimal. | 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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