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detect_cross_language_apis

Identify REST, GraphQL, gRPC, WebSocket, and WebAssembly APIs across multiple languages using framework-specific pattern recognition.

Instructions

Detect API endpoints, services, and schemas across all supported languages. Identifies REST APIs, GraphQL schemas, gRPC services, WebSocket endpoints, and WebAssembly modules with framework-specific pattern recognition.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_typesNoFilter by specific API types (optional - detects all types if not specified)
min_confidenceNoMinimum confidence threshold for API detection (default: 0.3)
include_schemasNoInclude schema files (OpenAPI, GraphQL, proto, WASM) in results (default: true)
Behavior2/5

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

No annotations provided; description carries full burden. It states what the tool does but does not disclose behavioral traits such as whether it requires permissions, modifies state, or has limitations (e.g., performance on large projects). No side effects mentioned.

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

Conciseness5/5

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

Two concise sentences with no wasted words. Front-loaded with the main action and followed by specifics. Every sentence adds value.

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

Completeness3/5

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

Given the variety of API types and no output schema, the description could be more complete. It does not explain the return format or structure, which would help an agent process results. However, it covers the core functionality adequately.

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?

Schema coverage is 100%; parameters are documented in the schema. Description adds context about what each API type is (REST APIs, GraphQL schemas, etc.) but does not add significant meaning beyond schema descriptions.

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?

Description clearly states it detects API endpoints, services, and schemas across all supported languages, listing specific types (REST, GraphQL, gRPC, WebSocket, WebAssembly). It distinguishes from sibling tools like detect_cross_language_deps and detect_enhanced_frameworks by focusing on APIs.

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

Usage Guidelines3/5

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

Description implies this tool is for detecting APIs but does not explicitly state when to use it versus alternatives like detect_cross_language_deps or detect_enhanced_frameworks. No guidance on when not to use.

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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