ideogram-rate-limits
Implement Ideogram rate limiting, backoff, and request queuing patterns. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Ideogram. Trigger with phrases like "ideogram rate limit", "ideogram throttling", "ideogram 429", "ideogram retry", "ideogram backoff", "ideogram queue".
84
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 well-crafted skill description that clearly defines its scope (Ideogram rate limiting and request management), provides explicit 'Use when' guidance, and includes a comprehensive list of natural trigger terms. It follows third-person voice correctly and is concise without being vague. It serves as a strong example of how to write a skill description for a narrowly-scoped, API-specific task.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: rate limiting, backoff, and request queuing patterns. Also mentions retry logic and optimizing API request throughput. | 3 / 3 |
Completeness | Clearly answers both 'what' (implement rate limiting, backoff, and request queuing for Ideogram) and 'when' (explicit 'Use when' clause covering rate limit errors, retry logic, and throughput optimization, plus explicit trigger phrases). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms including 'ideogram rate limit', 'ideogram throttling', 'ideogram 429', 'ideogram retry', 'ideogram backoff', 'ideogram queue' — these are terms users would naturally use when encountering these issues. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — scoped specifically to Ideogram API rate limiting patterns. The combination of 'Ideogram' + rate limiting/backoff/queuing creates a very clear niche unlikely to conflict with other 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 TypeScript code covering multiple rate-limiting patterns for Ideogram's API. Its main strengths are concrete, copy-paste-ready code and a clear error handling reference table. Weaknesses include verbosity from including four separate patterns inline without splitting to reference files, and missing explicit validation/verification steps in the batch workflow.
Suggestions
Add explicit validation checkpoints in the batch workflow (e.g., verify response contains expected image data before counting as success, add a summary verification step after batch completion).
Consider moving the Token Bucket and Batch Processing patterns into separate referenced files to improve progressive disclosure and reduce the main skill's token footprint.
Remove the 'Prerequisites' and 'Output' sections — Claude already understands async patterns, and the output section merely restates what the code demonstrates.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good use of tables and code, but includes some unnecessary elements like the 'Prerequisites' section (Claude knows async patterns), the 'Output' section restating what the code already demonstrates, and the Token Bucket implementation which adds significant length for a pattern that overlaps with the queue approach. The overview explanation of concurrent vs per-minute is genuinely useful though. | 2 / 3 |
Actionability | All four steps provide fully executable TypeScript code with concrete API endpoints, headers, error handling, and configuration values. The code is copy-paste ready with real Ideogram API URLs, proper error status checks, and practical defaults like concurrency of 8 to leave headroom. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced, and the error handling table provides good decision guidance. However, there are no explicit validation checkpoints — for batch operations involving API calls, there's no verification step (e.g., checking response data integrity, validating generated images) and no feedback loop for the batch process beyond logging counts. The scoring notes specify missing feedback loops in batch operations should cap at 2. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and tables, but it's quite long (~150 lines of code) with all patterns inline. The Token Bucket and Batch Processing sections could be split into separate reference files. There's a reference to 'ideogram-security-basics' 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 | |
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