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code_snippets

Read-only

Generate runnable curl, JavaScript, and Python samples for every operation, with path params filled in and a realistic body.

Input Schema

NameRequiredDescriptionDefault
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
documentYesThe API description to operate on — OpenAPI, AsyncAPI, Arazzo or JSON Schema. A YAML/JSON string or an already-parsed object; both are accepted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / context
      Added value: +{
      +  "description": "Optional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.",
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • addedInput schema / properties / document
      Added value: +{
      +  "description": "The API description to operate on — OpenAPI, AsyncAPI, Arazzo or JSON Schema. A YAML/JSON string or an already-parsed object; both are accepted.",
      +  "type": [
      +    "string",
      +    "object"
      +  ]
      +}
  3. Added

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful output context ('runnable', path params filled in, realistic body) but says nothing about snippet count, ordering, or how bodies are derived, so it only modestly exceeds the annotations.

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?

One sentence, front-loaded with the verb and output artifacts, and every clause ('runnable', 'path params filled in', 'realistic body') adds information rather than restating the name.

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?

For a two-parameter read-only generation tool with a fully documented schema and no output schema, the description covers what is produced and in what languages. It stops short of describing the returned structure (e.g., one snippet per operation, grouped by language), which is the only notable gap.

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 description coverage is 100% for both parameters (document and context are both fully documented in the schema), so the baseline of 3 applies. The description adds no format or syntax detail for the document parameter beyond what the schema already states.

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?

States a specific verb (generate) and a concrete resource (curl, JavaScript, and Python samples) with a scope modifier ('for every operation'), so an agent immediately knows what comes out. It does not, however, name or differentiate itself from plausible siblings like mock_payloads or forge_mcp_tools.

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?

There is no when-to-use guidance, no statement of when this is preferable to mock_payloads or the other generation tools, and no prerequisites mentioned. Usage must be inferred purely from the fact that it emits code samples.

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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