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Get REQ example

get_req_example

Returns a complete, valid sample requirement document as raw markdown, including frontmatter and body, to serve as a learning example for SpecMgr structures.

Instructions

Return a complete, valid sample requirement document as raw markdown -- frontmatter and body -- exercising every section, for use as a learning example.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.36.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden, and it does say the output is raw markdown containing both frontmatter and body, and that the sample exercises every section. That is genuinely useful context, but for a parameterless static fetch there is little more to disclose (no auth, pagination, or side effects are mentioned, and none are implied by "Return").

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?

A single dense sentence with the return format front-loaded ("raw markdown") and the purpose trailing. No filler or redundancy, though the em-dash aside slightly loosens an otherwise tight line.

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?

An output schema exists, so the description need not enumerate return contents, and with no parameters and no annotations there are few behavioral facts to cover. It supplies the format and the sample-completeness guarantee, leaving only sibling routing unaddressed.

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

Parameters4/5

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

The tool takes zero parameters, so the schema has nothing to document and the description cannot add parameter meaning. Baseline 4 applies for a parameterless definition.

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 uses a concrete verb ("Return") and a specific resource ("sample requirement document"), and the phrase "for use as a learning example" separates it from near-name siblings like get_req_template and get_req. It stops short of naming those alternatives explicitly, so an agent must infer the distinction from the name.

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?

"For use as a learning example" hints at the intended situation, but the description never states when to pick this over get_req, get_req_template, or the parallel *_example tools, and lists no exclusions. Usage is implied rather than guided.

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