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gemini-api-dev

The Gemini API provides access to Google's most advanced AI models. Key capabilities include:

47

Quality

50%

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SecuritybySnyk

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/gemini-api-dev/SKILL.md

The canonical home for this skill is gemini-api-dev in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

61%Weight 40%Scale 1-5

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

The body is actionable and well-structured, giving executable quick-start code and exact authoritative references for a fast-moving API. Its main weaknesses are moderate verbosity from the repeated multi-language quick start and the lack of validation checkpoints in its documentation-discovery workflow.

Suggestions

Collapse or condense the three near-identical language quick starts (e.g. show one full example and link the others) to reduce token weight.

Move the long documentation-link list and model table into a separate reference file so SKILL.md stays a lean overview.

Add explicit verification guidance for the discovery workflow (e.g. confirm the spec version, re-fetch llms.txt when a page is missing) to add the missing checkpoints.

DimensionReasoningScore

Conciseness

The body is mostly efficient with bullets and tight code, but the triple-language quick start, the inline doc-page link list, and the discovery-spec boilerplate could be tightened; it does not over-explain basic concepts, placing it at the mostly-efficient-but-could-be-tighter anchor.

3 / 5

Actionability

It provides copy-paste-ready quick-start code in three languages plus exact install commands, discovery-spec URLs, and an llms.txt URL — concrete and mostly executable, with the minor gap that only the simplest generate_content case is shown while other listed capabilities are deferred to external docs.

4 / 5

Workflow Clarity

A discovery sequence is present (use the spec as source of truth; fetch llms.txt; fetch specific pages) with a numbered list, but there are no validation checkpoints and the steps are implicit, matching the score-3 anchor of steps present with checkpoint gaps; the destructive-operation cap does not apply to this reference-style skill.

3 / 5

Progressive Disclosure

Content is well-sectioned (Overview, Models, SDKs, Quick Start, API spec, How to use) with clearly signaled, one-level-deep external references (doc-page links and the llms.txt index) and no nesting; it is not score 5 because the doc-link list and model table are inlined in SKILL.md rather than split into a reference file.

4 / 5

Total

14

/

20

Passed

Description

40%Weight 40%Scale 1-5

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 truncated mid-sentence and defers its capability list to the body, leaving a weak "what" and no "when to use" guidance. Its one strength is a specific, natural trigger term ("Gemini API") that keeps it reasonably distinct from other skills.

Suggestions

Complete the description sentence and inline the key capabilities instead of trailing off with "Key capabilities include:".

Add an explicit "Use when ..." clause naming concrete trigger phrases (e.g. "Use when integrating Google's Gemini models, generating text/images, or doing function calling with the Gemini API").

Include synonyms and model-name variants users say naturally (e.g. "Google AI", "Gemini Pro/Flash") to broaden trigger coverage.

DimensionReasoningScore

Specificity

The description names the domain ("The Gemini API provides access to Google's most advanced AI models") but states no concrete actions, trailing off with "Key capabilities include:"; it matches the anchor that names the domain with minimal/generic actions rather than listing specific capabilities.

2 / 5

Completeness

It offers only a vague, literally incomplete "what" (the sentence ends in a colon with capabilities deferred to the body) and no "when to use" trigger guidance, matching the score-2 anchor of a vague "what" with no "when".

2 / 5

Trigger Term Quality

"Gemini API" is a specific natural keyword a user would actually say, comparable to the score-3 anchor, but no synonyms or variations (e.g. "Google AI", "Gemini models", model names) are present.

3 / 5

Distinctiveness Conflict Risk

"The Gemini API provides access to Google's most advanced AI models" carves a clear niche distinct from most skills with only minor overlap risk against generic Google-AI or LLM-API skills, fitting the mostly-distinct score-4 anchor; it is not score 5 because no explicit distinct trigger phrases are given.

4 / 5

Total

11

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20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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