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api_swarm

Execute parallel HTTP API requests to fetch or send data simultaneously, optimizing workflows for AI agent orchestration and data processing tasks.

Instructions

Execute parallel HTTP API requests.
requests: JSON array of {url, method?, headers?, body?}
Example: [{"url": "https://api.example.com/data"}, {"url": "...", "method": "POST", "body": "{}"}]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestsYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'parallel HTTP API requests' but doesn't explain concurrency limits, error handling, timeout behavior, authentication requirements, or response format. For a tool that executes multiple HTTP requests, this is a significant gap in transparency.

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?

The description is highly concise and well-structured: one sentence states the purpose, followed by a clear parameter explanation and a practical example. Every sentence earns its place without redundancy, making it easy to parse and understand quickly.

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

Completeness2/5

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

Given the complexity of executing parallel HTTP requests, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks information on behavioral traits (e.g., error handling, rate limits), output format, and usage guidelines. This makes it inadequate for safe and effective tool invocation in a production context.

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 description adds meaningful context for the 'requests' parameter by providing an example JSON array structure with fields like url, method, headers, and body. However, with 0% schema description coverage and one parameter, the description compensates somewhat but doesn't fully detail syntax constraints (e.g., JSON validation, required fields beyond url). The baseline is 3 due to the example adding value beyond the bare schema.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Execute parallel HTTP API requests.' It specifies the verb ('execute') and resource ('parallel HTTP API requests'), making the function unambiguous. However, it doesn't distinguish this tool from sibling swarm tools like 'code_gen_swarm' or 'deploy_swarm', which limits it to a 4 rather than a 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where parallel HTTP requests are appropriate, prerequisites, or comparisons to other swarm tools or standard single-request methods. This lack of context leaves the agent without usage direction.

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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