Get VCR example

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

No annotations, so the description carries the burden, and it discloses two meaningful traits: the output is raw markdown (frontmatter plus body) and covers every section. It doesn't state whether the data is live or static, but otherwise covers what an agent needs to know about the return.

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 compact sentence front-loads the verb and resource, then qualifies format and scope with no waste.

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 return-value details needn't be spelled out. The description supplies the key missing context — markdown format and exhaustive section coverage — good enough for a static example tool, though it could note that the output is not real record data.

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?

Zero parameters, so parameter semantics is trivially complete. Baseline 4 for no-params tools.

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?

States a specific verb+resource (return a sample VCR record document) and describes the content ('exercising every section'). It clearly distinguishes itself from get_vcr (the actual record) and get_vcr_template (the blank template), though the prefixed naming convention already signals this.

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?

The phrase 'for use as a learning example' implies the when-to-use context (study/learn format vs. fetch real data), but there are no explicit exclusions or named alternatives like get_vcr or get_vcr_template.

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