firecrawl-architecture-variants
Choose and implement Firecrawl architecture patterns for different scales and use cases. Use when designing new Firecrawl integrations, choosing between on-demand/scheduled/pipeline architectures, or planning scraping infrastructure. Trigger with phrases like "firecrawl architecture", "firecrawl blueprint", "how to structure firecrawl", "firecrawl at scale", "firecrawl pipeline design".
68
83%
Does it follow best practices?
Impact
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No eval scenarios have been run
Advisory
Suggest reviewing before use
Quality
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 solid skill description that clearly defines its niche around Firecrawl architecture planning and implementation. It excels at completeness with explicit 'Use when' and 'Trigger with' clauses, and has strong distinctiveness. The main weakness is that the specific capabilities could be more concrete—listing actual architecture patterns or specific deliverables rather than staying at the 'choose and implement' level.
Suggestions
Add more concrete specific actions, e.g., 'Designs on-demand crawl endpoints, configures scheduled batch pipelines, sets up webhook-based async architectures, implements rate-limited queue systems' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Firecrawl architecture patterns) and some actions (choose, implement, design integrations, plan scraping infrastructure), but doesn't list multiple concrete specific actions like 'configure batch crawling, set up webhook pipelines, implement rate limiting strategies'. The actions remain somewhat high-level. | 2 / 3 |
Completeness | Clearly answers both 'what' (choose and implement Firecrawl architecture patterns for different scales and use cases) and 'when' (designing new integrations, choosing between architectures, planning scraping infrastructure) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes explicit trigger phrases that users would naturally say: 'firecrawl architecture', 'firecrawl blueprint', 'how to structure firecrawl', 'firecrawl at scale', 'firecrawl pipeline design'. Also includes natural terms like 'on-demand/scheduled/pipeline architectures' and 'scraping infrastructure'. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting Firecrawl architecture patterns specifically. The combination of 'Firecrawl' + 'architecture/blueprint/pipeline design' creates a clear, distinct trigger space that is unlikely to conflict with general web scraping skills or other Firecrawl skills focused on basic usage. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured architectural guide with excellent actionability—all three patterns include executable, production-ready TypeScript code with real Firecrawl SDK usage. The decision matrix and decision tree provide clear guidance for choosing architectures. The main weakness is that the skill is quite long due to three substantial code blocks that could benefit from being split into separate files, and some content slightly overlaps between the matrix and inline descriptions.
Suggestions
Consider splitting each architecture's full code example into separate referenced files (e.g., on-demand.ts, scheduled-pipeline.ts, realtime-pipeline.ts) and keeping only minimal snippets inline to improve progressive disclosure and reduce SKILL.md length.
Remove the 'Best for' lines under each architecture heading since the decision matrix already captures this information, improving conciseness.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient and avoids explaining basic concepts, but the three full architecture code blocks are quite lengthy. Some inline comments and the 'Best for' lines add minor redundancy with the decision matrix. The ASCII diagrams are useful but the overall content could be tightened. | 2 / 3 |
Actionability | All three architectures include fully executable TypeScript code with concrete API calls, configuration patterns, and usage examples. The code is copy-paste ready with real Firecrawl SDK methods, specific options, and practical patterns like credit budgeting and content validation. | 3 / 3 |
Workflow Clarity | Each architecture has a clear visual flow diagram, well-sequenced steps, and the real-time pipeline includes explicit validation (content length check, captcha detection) and error recovery via the error handling table. The decision tree at the end provides clear guidance for choosing between architectures. The scheduled pipeline includes polling for completion status. | 3 / 3 |
Progressive Disclosure | The skill has good structural organization with a decision matrix, three architectures, and a decision tree. However, the three large code blocks make this a lengthy monolithic file. The architecture code examples could be split into separate referenced files. References to external docs and the pitfalls skill are present but minimal. | 2 / 3 |
Total | 10 / 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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