ideogram-webhooks-events
Build event-driven workflows around Ideogram's synchronous API. Use when implementing async generation queues, batch processing, callback patterns, or image processing pipelines. Trigger with phrases like "ideogram webhook", "ideogram events", "ideogram async", "ideogram queue", "ideogram batch pipeline".
80
77%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/ideogram-pack/skills/ideogram-webhooks-events/SKILL.mdQuality
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 description with excellent trigger term coverage and clear completeness, explicitly addressing both what the skill does and when to use it. Its main weakness is that the capabilities described are somewhat abstract (architectural patterns like 'callback patterns' and 'batch processing') rather than listing concrete, specific actions the skill performs. The description is well-structured and distinctive.
Suggestions
Replace abstract pattern names with more concrete actions, e.g., 'Creates async job queues for Ideogram image generation, implements polling-based status checking, builds batch processing pipelines with retry logic' instead of generic pattern names.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Ideogram API, event-driven workflows) and some actions (async generation queues, batch processing, callback patterns, image processing pipelines), but these are more architectural patterns than concrete actions. It doesn't specify what the skill actually produces or does step-by-step (e.g., 'creates queue workers', 'sets up webhook endpoints'). | 2 / 3 |
Completeness | Clearly answers both 'what' (build event-driven workflows around Ideogram's synchronous API) and 'when' (implementing async generation queues, batch processing, callback patterns, or image processing pipelines), with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases like 'ideogram webhook', 'ideogram events', 'ideogram async', 'ideogram queue', 'ideogram batch pipeline'. These are terms a user would naturally use when seeking this functionality, and the coverage of variations is good. | 3 / 3 |
Distinctiveness Conflict Risk | The combination of 'Ideogram' + 'event-driven/async/webhook/queue' creates a very specific niche. The trigger terms are all prefixed with 'ideogram', making it unlikely to conflict with generic async processing or other image API skills. | 3 / 3 |
Total | 11 / 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, highly actionable skill with complete, executable TypeScript examples covering async patterns around Ideogram's API. Its main weaknesses are verbosity (the full inline code could be split or trimmed) and missing explicit validation checkpoints in the workflow, particularly for batch operations where verification of successful generation and storage would be important.
Suggestions
Add explicit validation checkpoints: verify Redis connectivity before starting, verify image file was written after download, and add a batch completion verification step that checks all jobs succeeded.
Trim the overview paragraph — remove the explanation of what synchronous means and the 5-15 second timing detail, which Claude can infer from context.
Consider moving the full worker implementation and batch generation code to separate referenced files, keeping only the key patterns and queue setup inline in SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The overview paragraph explains what synchronous means and provides context Claude already knows. The code examples are mostly lean but the skill is quite long (~150 lines of code) with some redundancy. The 'Output' section just restates what was already covered. | 2 / 3 |
Actionability | All code examples are fully executable TypeScript with proper imports, types, and realistic configurations. The BullMQ setup, callback handler, batch generation, and sharp pipeline are all copy-paste ready with concrete values. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced (queue → callback → batch → post-processing) and the error handling table is useful. However, there are no explicit validation checkpoints — no step to verify Redis is running, no verification that images were actually saved correctly, and no feedback loop for batch operations beyond BullMQ's built-in retry. | 2 / 3 |
Progressive Disclosure | The skill has good section structure and references external resources, but the inline code is very long and could benefit from splitting detailed implementations into separate files. The 'Next Steps' reference to ideogram-performance-tuning is good but the main content is monolithic. | 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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