ideogram-observability
Set up monitoring, metrics, and alerts for Ideogram integrations. Use when implementing observability for Ideogram operations, tracking costs, or configuring alerting for generation health. Trigger with phrases like "ideogram monitoring", "ideogram metrics", "ideogram observability", "monitor ideogram", "ideogram alerts", "ideogram dashboard".
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-observability/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 defines its scope (monitoring/observability for Ideogram integrations), provides explicit trigger phrases, and answers both what and when. The main weakness is that the specific capabilities could be more granular — listing concrete actions like dashboard creation, cost threshold alerts, or latency tracking would strengthen specificity.
Suggestions
Add more concrete actions to improve specificity, e.g., 'create Prometheus/Grafana dashboards, define cost threshold alerts, track generation latency and error rates, set up webhook notifications for failures'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (monitoring/metrics/alerts for Ideogram integrations) and some actions (set up monitoring, track costs, configure alerting), but doesn't list multiple concrete specific actions like 'create dashboards, define SLOs, set up cost tracking alerts, configure latency monitors'. | 2 / 3 |
Completeness | Clearly answers both 'what' (set up monitoring, metrics, and alerts for Ideogram integrations) and 'when' (implementing observability, tracking costs, configuring alerting) with explicit trigger phrases listed. | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases including 'ideogram monitoring', 'ideogram metrics', 'ideogram observability', 'monitor ideogram', 'ideogram alerts', 'ideogram dashboard' — good coverage of terms users would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining 'Ideogram' (a specific service) with 'monitoring/observability' — very unlikely to conflict with other skills due to the narrow domain intersection. | 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 skill with concrete executable code, well-defined metrics, and complete alerting rules. Its main weaknesses are the lack of validation checkpoints in the workflow (e.g., verifying metrics emission before deploying alerts) and the monolithic structure that puts all detailed code inline rather than using progressive disclosure. The content could be tightened by removing some intermediate explanations and splitting detailed implementations into referenced files.
Suggestions
Add a validation step after Step 1 (e.g., 'Run a test generation and verify the JSON metric output appears in stdout before proceeding') to ensure the instrumentation pipeline works.
Split the detailed Prometheus metrics setup and alerting rules into a separate referenced file (e.g., PROMETHEUS_SETUP.md) to keep the main skill leaner and improve progressive disclosure.
Add a brief verification step after deploying alerting rules (e.g., 'Trigger a test alert by temporarily lowering thresholds and confirming notification delivery').
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good use of tables and code, but is somewhat lengthy. The cost estimation section and some wrapper code could be tightened. The overview is lean, but the overall document is verbose for what could be a more focused skill. | 2 / 3 |
Actionability | Fully executable TypeScript code for the instrumented wrapper, Prometheus metrics setup, and complete YAML alerting rules. The Grafana queries are copy-paste ready. Cost estimation includes concrete per-model pricing. | 3 / 3 |
Workflow Clarity | Steps are clearly numbered and sequenced from instrumentation through alerting and dashboards. However, there are no validation checkpoints—no step to verify metrics are being emitted correctly, no test generation to confirm the pipeline works end-to-end before deploying alerts. | 2 / 3 |
Progressive Disclosure | The content is largely monolithic with all code inline. The Prometheus section is marked 'Optional' which is good, but the detailed wrapper code, cost estimation, alerting rules, and dashboard queries could benefit from being split into referenced files. The 'Next Steps' reference to an incident runbook is a good pattern but underutilized. | 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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