Name: firebase-ai-logic-basics
Rating: 72.33000000000001 (1 reviews)
Author: firebase

firebase-ai-logic-basics

Official skill for integrating Firebase AI Logic (Gemini API) into web applications. Covers setup, multimodal inference, structured output, and security.

3.33x

Quality

—

Does it follow best practices?

Impact

100%

3.33x

Average score across 2 eval scenarios

Securityby

Advisory

Suggest reviewing before use

Quality

Content

57%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is well-structured with effective progressive disclosure to real reference files, but core capabilities lack inline executable examples and the workflow has no validation checkpoints, capping actionability and workflow clarity at 2.

Suggestions

Add short, copy-paste-ready code snippets for the core capabilities (text generation, multimodal, chat, streaming, structured output) rather than one-line descriptions.

De-duplicate the 'Use current model names' warning so it appears once, and trim the Overview's explanation of what Firebase AI Logic is.

Add a validation step after `init ailogic` (e.g., verify the Gemini Developer API is enabled / apps:list shows an app) before directing the user to capabilities.

Dimension	Reasoning	Score
Conciseness	The body is organized into lean sections, but the 'Use current model names' warning is repeated near-verbatim (Core Capabilities and Initialization Code References) and the Overview explains what Firebase AI Logic is — material that could be tightened.	2 / 3
Actionability	Setup provides concrete commands (npm install, npx firebase-tools init ailogic), but the core capabilities (text generation, multimodal, chat, streaming, structured output) are described in one-liners with no inline executable code; the actual code lives only in referenced files.	2 / 3
Workflow Clarity	Setup steps are sequenced (prerequisites -> install -> init) but there are no validation checkpoints or feedback loops to confirm initialization succeeded before proceeding to capabilities.	2 / 3
Progressive Disclosure	SKILL.md is a concise overview that signals one-level-deep references to real bundle files (verified: references/ios_setup.md, flutter_setup.md, usage_patterns_web.md, usage_patterns_android.md all exist) via a dedicated References section and a context table.	3 / 3
	Total	9 / 12 Passed

Description

82%

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 is specific and well-targeted with strong trigger terms, but it omits an explicit 'Use when...' trigger clause, leaving the 'when to use it' half only implicit.

Suggestions

Add an explicit 'Use when...' clause stating when to invoke the skill (e.g., 'Use when integrating Gemini into a web or mobile app, or when the user mentions Firebase AI Logic, Vertex AI for Firebase, or the Gemini API').

Clarify platform breadth in the description since the body covers Android/iOS/Flutter/Web, not just web applications.

Dimension	Reasoning	Score
Specificity	Names the domain ('integrating Firebase AI Logic (Gemini API) into web applications') and lists multiple concrete capabilities ('setup, multimodal inference, structured output, and security'), matching the anchor for multiple specific concrete actions.	3 / 3
Completeness	Clearly answers 'what does this do' but has no 'Use when...' clause or equivalent explicit trigger guidance, which per the guidelines caps completeness at 2.	2 / 3
Trigger Term Quality	Includes natural terms a user would say — 'Firebase AI Logic', 'Gemini API', 'web applications', 'multimodal inference', 'structured output' — giving good coverage of likely phrasings.	3 / 3
Distinctiveness Conflict Risk	Targets a clear, specific niche (Firebase AI Logic / Gemini API integration) with distinct triggers unlikely to collide with other skills.	3 / 3
	Total	11 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: firebase/agent-skills
Commit: 538130c

Reviewed: 16 days ago

Table of Contents

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