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Get TXT example

get_txt_example

Return a complete sample free-form text document as raw markdown. It includes frontmatter, free H2/H3 headings, a list, a reference line, and two ordered Updates entries for learning.

Instructions

Return a complete, valid sample free-form text document as raw markdown -- frontmatter and body -- exercising the free-form body (free H2/H3 headings, a list, a free-floating reference line) and the mandatory ## Updates log with two ordered entries, for use as a learning example.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.38.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the disclosure burden. It does state the return format ('raw markdown -- frontmatter and body') and the structural content of the payload, which is genuinely useful. It does not say the operation is side-effect free or that the sample is static, but for a zero-argument retrieval of a canned document those are low-stakes omissions.

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?

A single sentence, front-loaded with the verb and return format, then the content detail. The dense parenthetical listing is doing real work by telling the agent what the example demonstrates, so nothing is filler.

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?

With an output schema present and zero parameters, the description needn't explain return values, and it nonetheless characterizes the sample's shape. What it leaves out is the relationship to the sibling template, schema, and CRUD tools, which is the one thing an agent might still puzzle over.

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 no parameters, so the baseline of 4 applies. The description correctly implies nothing is configurable, and the agent need not reason about arguments at all.

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 specific verb and resource: 'Return a complete, valid sample free-form text document as raw markdown -- frontmatter and body'. It goes further, enumerating the content the sample exercises (free H2/H3 headings, a list, a reference line, a mandatory `## Updates` log with two ordered entries), so an agent knows exactly what will come back. It does not name the neighbouring `get_txt_template` or `get_txt_schema` to draw the contrast, which keeps it below 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 Guidelines3/5

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

The phrase 'for use as a learning example' implies the intended context, but it is stated as a rationale rather than as an instruction. There is no explicit 'use this when you need to see a valid document' versus 'use get_txt_template when you need a skeleton to fill in'. The distinction from the many sibling example/schema/template tools is left to be inferred from the names.

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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