Get FEAT example

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return format (raw markdown with frontmatter and body, exercising every section) and implies a read-only, parameterless fetch, but it says nothing about whether the output is static or whether it costs anything to call. It covers the essentials without richness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence that identifies the action, the format, and the purpose with no filler.

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

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 explain return values, and it still characterizes the payload as complete raw markdown covering every section. For a zero-parameter sample getter this is nearly everything an agent needs, with sibling differentiation the only real gap.

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

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

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies.

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

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

Names a specific verb and resource (return a sample feature document) and states the artifact's shape (frontmatter plus body, every section). The phrase 'for use as a learning example' implicitly distinguishes it from get_feat/get_feat_template, but the description never names those alternatives, so differentiation is left to inference.

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

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

'for use as a learning example' implies the intended context, but there is no explicit when-to-use guidance and no statement of when to prefer get_feat_template or get_feat instead. Adequate but inferential.

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