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api_executor

Execute a live HTTP request to an external URL. Returns real status, headers, and response body. Private IPs are blocked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL (https required)
bodyNo
methodYes
headersNo
timeout_msNo

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the burden of transparency. It discloses the live nature, external URL scope, private IP blocking, and return contents, but omits details like authentication, rate limits, redirect behavior, and error handling. This is moderate added value but not comprehensive.

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 sentences, front-loaded with the core purpose, and a concise safety note. No wasted words, and the structure is easy to parse.

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?

For a tool with no annotations or output schema, the description provides the essential purpose and a key constraint, but it lacks guidance on parameter formats, error handling, and edge cases like redirects or non-2xx responses. Adequate but incomplete for a network tool with five parameters.

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

Parameters2/5

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

Schema description coverage is only 20%, and the description does not explain the body, headers, or timeout parameters beyond what the schema offers. It focuses on outputs rather than input semantics, leaving significant gaps for a 5-parameter tool.

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 action ('Execute a live HTTP request') and its outputs ('real status, headers, and response body'), making it distinct from all sibling tools (code_generator, history_tracker, etc.). The additional constraint on private IPs adds useful context.

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

Usage Guidelines4/5

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

The description implicitly indicates when to use this tool (for live external URL requests) and notes a critical exclusion (private IPs are blocked). However, it does not explicitly compare to alternatives or state when not to use it beyond the IP restriction, so it falls short of a 5.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool addresses a distinct phase of the API playground workflow: parsing, rendering, executing, code generation, and history tracking. No two tools overlap in purpose, so an agent can select the right one without ambiguity.

Naming Consistency5/5

All tool names follow the same pattern: a domain noun combined with an agent suffix (e.g., api_executor, schema_parser, history_tracker). This consistent structure makes the set predictable and easy to navigate.

Tool Count5/5

The server has 5 tools, which is well within the ideal range. Each tool contributes a unique, essential capability to the playground experience, with no bloat or redundancy.

Completeness5/5

The tool set covers the entire lifecycle of building and using an API playground: parse a schema, render an interactive UI, execute live requests, generate code snippets, and inspect history. No obvious gaps or dead ends exist.