ideogram-reference-architecture
Implement Ideogram reference architecture with prompt templates, asset pipelines, and CDN delivery. Use when designing new Ideogram integrations, building brand asset systems, or establishing architecture for image generation at scale. Trigger with phrases like "ideogram architecture", "ideogram project structure", "ideogram brand assets", "ideogram pipeline design", "ideogram at scale".
80
77%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/ideogram-pack/skills/ideogram-reference-architecture/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 well-structured skill description that clearly identifies its niche (Ideogram reference architecture), provides explicit 'Use when' and 'Trigger with' clauses, and is highly distinctive. Its main weakness is that the capability actions are somewhat abstract and architectural rather than listing granular concrete operations, though this may be appropriate for an architecture-focused skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Ideogram) and some actions ('prompt templates, asset pipelines, CDN delivery'), but these are somewhat abstract architectural concepts rather than multiple concrete, granular actions like 'create prompt template files' or 'configure CDN endpoints'. | 2 / 3 |
Completeness | Clearly answers both 'what' (implement Ideogram reference architecture with prompt templates, asset pipelines, CDN delivery) and 'when' (designing new Ideogram integrations, building brand asset systems, establishing architecture for image generation at scale), with explicit trigger phrases. | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases like 'ideogram architecture', 'ideogram project structure', 'ideogram brand assets', 'ideogram pipeline design', 'ideogram at scale'. These are specific and cover multiple variations a user might naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific 'Ideogram' domain focus combined with architectural concerns like reference architecture, asset pipelines, and CDN delivery. Unlikely to conflict with generic image generation or other API integration 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, actionable reference architecture with executable TypeScript code covering multiple Ideogram API endpoints and a complete asset pipeline. Its main weaknesses are the lack of validation/feedback loops between pipeline steps (especially important for batch image generation) and the heavy inline code that could benefit from progressive disclosure to separate files. The content is mostly efficient but could trim the architecture diagram and redundant Output section.
Suggestions
Add explicit validation checkpoints between pipeline steps (e.g., verify downloaded image size/integrity before sharp processing, validate API response structure before accessing nested fields)
Consider moving the detailed code implementations to separate referenced files (e.g., TEMPLATES.md, PIPELINE.md) and keeping SKILL.md as a concise overview with quick-start examples
Add a feedback loop for generation quality: e.g., use Describe on generated output to verify it matches intent, retry with adjusted prompt if not
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly efficient but includes some unnecessary elements like the architecture diagram (which is nice but adds significant token cost), the error handling table with somewhat obvious entries, and the Output section that just restates what was already shown. The code examples themselves are well-structured but the overall document could be tightened. | 2 / 3 |
Actionability | The skill provides fully executable TypeScript code with concrete API calls, specific endpoint URLs, proper headers, request bodies, and file I/O. The prompt templates include real values for all fields, and the pipeline code is copy-paste ready with proper imports and error handling. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced (template → generate → pipeline → describe/remix) and the code includes some validation (response.ok check, URL expiration comment). However, there are no explicit validation checkpoints between steps, no feedback loops for error recovery (e.g., what if generation produces poor results), and no verification that downloaded images are valid before processing with sharp. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and a project structure reference, but it's quite long (~200 lines of code inline) when some of this could be referenced as separate files. The external references at the bottom are good, but the single 'Next Steps' reference to another skill is minimal. The project structure section hints at file separation but all code lives inline. | 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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