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gemini-api-integration

Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production best practices.

Quality

72%

Does it follow best practices?

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tessl review fix ./skills/gemini-api-integration/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%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.

A practical, code-heavy reference whose examples are largely copy-paste runnable for Node and Python. Its weaknesses are tutorial-style organization without validation loops, no use of reference files to split advanced content, and version-sensitive model guidance that will age poorly.

Suggestions

Move the version-sensitive model selection table into a dated reference file (or a deprecated/old-patterns section) so stale model names don't erode the core guidance.

Split troubleshooting and error handling into a references/ file, keeping SKILL.md to quick start, core patterns, and links — improving progressive disclosure and token budget.

Complete the function-calling example: show constructing the functionResponse part and sending it back to the model, and add explicit validation/retry checkpoints to the error-handling flow.

DimensionReasoningScore

Conciseness

The body is code-first and mostly tight, but the 'When to Use This Skill' section duplicates the description, and the version-pinned model table ('gemini-1.5-flash', 'gemini-2.0-pro') is time-sensitive with no dated or deprecated framing to keep it honest.

3 / 5

Actionability

Executable install commands and runnable Node/Python examples cover the common cases, but the function-calling example stops at a '// Send result back to model' comment with an undefined getWeather helper, leaving a key step unshown.

4 / 5

Workflow Clarity

Sections are numbered 1-7 but read as parallel feature tutorials rather than a sequenced process; validation checkpoints are absent and the error-handling guidance is illustrative rather than an explicit validate-and-retry loop.

3 / 5

Progressive Disclosure

The ~180-line body inlines everything — troubleshooting, the model table, and advanced examples — with no reference files or navigation to keep SKILL.md a lean overview.

3 / 5

Total

13

/

20

Passed

Description

75%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.

A solid description with an explicit 'Use when' clause and a concrete list of covered capabilities. Its main weaknesses are the vague 'production best practices' tail and a thin set of trigger synonyms and model-name keywords that users commonly mention.

Suggestions

Replace 'production best practices' with the concrete practices actually covered (e.g., 'retry/backoff for rate limits, API key handling, error diagnostics') to sharpen the 'what'.

Expand trigger terms with natural variations users say: 'gemini-pro', 'gemini-flash', 'Google AI Studio', 'gemini chat', or 'genai SDK'.

DimensionReasoningScore

Specificity

The description lists several specific capabilities ('model selection, multimodal inputs, streaming, function calling'), though 'production best practices' is generic filler and it names topics rather than concrete actions.

4 / 5

Completeness

Both what ('Covers model selection, multimodal inputs, streaming, function calling...') and when ('Use when integrating Google Gemini API into projects') are explicit, but the 'when' is a single condition that could be more specific with additional trigger phrases.

4 / 5

Trigger Term Quality

Natural terms users would say ('Gemini API', 'streaming', 'function calling', 'multimodal inputs') are present, but common variations like model names ('gemini-pro', 'flash'), 'Google AI Studio', 'genai', or 'chat' are missing.

4 / 5

Distinctiveness Conflict Risk

'Google Gemini API' carves a clear niche with distinct triggers, with only minor overlap risk against generic LLM-API-integration or Google Cloud skills.

4 / 5

Total

16

/

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.

Validation — 15 / 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

Path

skills/gemini-api-integration/SKILL.md

Reviewed

Table of Contents

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