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Platano78

Smart-AI-Bridge

by Platano78

review

Analyze code from your current context to receive structured findings, a quality score, and improvement suggestions. Supports security, performance, quality, and comprehensive checks.

Instructions

Review a code blob you already have in context and return structured findings + a quality score + improvement suggestions. Pass the code itself in content; this tool does not read any file from disk. Use when Claude already has the code in hand. For a review of a file Claude has NOT seen (so the file content stays out of context and a real tokens_saved figure is returned), use analyze_file with analysisType:'security' instead. For multiple AI perspectives on the same code, use council. Read-only: never writes to disk. Returns: {success, file_path, language, review_type, review (full review text from the LLM, includes findings + severity + suggestions), endpoint_used}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesCode content to review
languageNoProgramming language hint
file_pathNoFile path for context
review_typeNocomprehensive
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses key behavioral traits: 'this tool does not read any file from disk' and 'Read-only: never writes to disk.' It also outlines the return structure. A small gap is that it doesn't mention potential rate limits or token usage, but the critical safety aspects are covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than a single sentence but every clause earns its place: it covers purpose, usage context, alternatives, read-only behavior, and return format. It is well-structured and front-loaded, without redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple with 4 parameters and no output schema. The description supplies the return shape, emphasizes the content requirement, and names alternatives. It sufficiently equips the agent to select and invoke the tool correctly, though additional details about output size or review depth would push it to a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers 3 of 4 parameters (75% coverage), so the baseline is near-average. The description adds emphasis on passing code in `content` but does not elaborate on language or review_type beyond what the schema's enum provides. It provides only marginal extra semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb and resource: 'Review a code blob you already have in context and return structured findings + a quality score + improvement suggestions.' It distinguishes itself from siblings by explicitly naming analyze_file and council as alternatives for different use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance ('Use when Claude already has the code in hand'), when-not-to-use (for files not seen, use analyze_file), and when to use an alternative (council for multiple perspectives). It also clarifies what to pass in the content parameter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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