genkit-production-expert
Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go. Deploy to Firebase Functions or Cloud Run with AI monitoring. Use when asked to "create genkit flow" or "implement RAG". Trigger with relevant phrases based on skill purpose.
42
43%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/ai-ml/jeremy-genkit-pro/skills/genkit-production-expert/SKILL.mdQuality
Discovery
67%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description covers a specific technology (Firebase Genkit) and provides a reasonable overview of capabilities with an explicit 'Use when' clause. However, it is weakened by the meaningless filler sentence 'Trigger with relevant phrases based on skill purpose' which adds no value, and the trigger terms could be more comprehensive to cover natural user language variations.
Suggestions
Remove the filler sentence 'Trigger with relevant phrases based on skill purpose' and replace it with actual trigger terms users would say, such as 'retrieval augmented generation', 'genkit plugin', 'AI agent flow', 'genkit indexer', 'genkit retriever'.
Expand the 'Use when' clause to cover more natural user phrases like 'build an AI pipeline with Genkit', 'set up RAG with Firebase', 'deploy genkit to cloud run', or 'add AI monitoring to my app'.
Make capabilities more concrete by specifying actions like 'define retrievers and indexers for RAG, chain prompts in multi-step flows, register custom tools, configure AI model plugins' instead of high-level categories.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Firebase Genkit) and lists some actions (RAG systems, multi-step flows, tool calling, deploy), but the actions are more like feature categories than concrete specific operations. 'Build production Firebase Genkit applications' is somewhat vague. | 2 / 3 |
Completeness | Answers both 'what' (build Genkit apps with RAG, flows, tool calling; deploy to Firebase/Cloud Run) and 'when' (explicitly says 'Use when asked to create genkit flow or implement RAG'). The 'when' clause is present and explicit, though somewhat narrow. | 3 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'genkit flow', 'RAG', 'Firebase Functions', 'Cloud Run', but the final sentence 'Trigger with relevant phrases based on skill purpose' is meaningless filler. Missing natural variations users might say like 'AI pipeline', 'retrieval augmented generation', 'genkit plugin', or 'AI monitoring dashboard'. | 2 / 3 |
Distinctiveness Conflict Risk | Firebase Genkit is a fairly specific niche, which helps distinctiveness. However, terms like 'RAG systems', 'tool calling', and 'AI monitoring' could overlap with other AI/LLM framework skills. The generic 'Trigger with relevant phrases based on skill purpose' adds no distinctiveness. | 2 / 3 |
Total | 9 / 12 Passed |
Implementation
20%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a high-level project brief or documentation outline than an actionable skill for Claude. It covers a broad scope (three languages, multiple deployment targets, RAG, tools, agents) but provides no executable code, no concrete implementation patterns, and defers all real content to reference files that don't exist. The verbose descriptions of concepts Claude already understands waste significant token budget.
Suggestions
Add at least one complete, executable code example for a basic Genkit flow (e.g., a TypeScript flow with Zod schema, model config, and ai.defineFlow()) — this is the most critical gap.
Remove or drastically shorten the Prerequisites and Overview sections, which explain things Claude already knows; replace with a compact 'Required packages' install command.
Add explicit validation checkpoints in the workflow: e.g., 'Verify schema compiles with tsc --noEmit', 'Confirm flow runs in Developer UI before deploying', 'Validate deployment with a test invocation'.
Either provide the referenced bundle files (how-it-works.md, workflow-examples.md, etc.) or inline the essential content — currently all actionable detail is deferred to nonexistent files.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is verbose and padded with information Claude already knows. The Overview restates the description, Prerequisites lists obvious requirements (Node.js, Python, Go runtimes), and sections like Resources explain what Zod is. The Examples section describes scenarios without providing any actual code, wasting tokens on narrative descriptions. | 1 / 3 |
Actionability | Despite covering a complex topic, there is zero executable code anywhere in the skill. Instructions are abstract directives like 'Implement the Genkit flow using ai.defineFlow()' without showing how. Examples describe scenarios narratively but provide no code. All concrete guidance is deferred to reference files that don't exist in the bundle. | 1 / 3 |
Workflow Clarity | The 10-step instruction sequence provides a reasonable ordering from project setup through deployment, and the error handling table is a useful addition. However, there are no validation checkpoints or feedback loops between steps — no 'verify schema compiles,' no 'confirm local test passes before deploying,' which is critical for a multi-step deployment workflow. | 2 / 3 |
Progressive Disclosure | The skill references four external files (how-it-works.md, production-best-practices-applied.md, errors.md, workflow-examples.md) which is good structure in principle. However, none of these files exist in the bundle, making the references unverifiable. The main file also contains substantial inline content (error table, full examples section) that could be better balanced with the referenced files. | 2 / 3 |
Total | 6 / 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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