fastmean_list_examples

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds the meaningful behavioral fact that results are paths intended as inputs to later calls, but says nothing about match semantics (case sensitivity, whether empty query lists everything, ordering).

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 with the action first and the follow-up usage hint second. No filler, nothing to trim.

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 values need no explanation, and annotations cover safety. What remains missing for a list tool is the empty-query/default behavior and match semantics, which an agent needs to call it correctly with zero or partial arguments.

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?

Schema coverage is 0% and the single parameter 'query' is documented nowhere else, so the description must carry the load. 'By substring' does explain the matching semantics of query, but it never states that query is optional with an empty default or what happens when it is omitted (presumably listing all examples).

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 ('Find') and resource ('installed example SCM files') plus the matching mode ('by substring'), so the agent knows exactly what is returned. It does not explicitly distinguish itself from the sibling fastmean_example (which presumably loads one example), leaving that differentiation 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?

The clause 'use returned paths in analysis' gives a useful downstream workflow hint, implying this is a discovery step before fastmean_example / fastmean_read_data. There is no explicit statement of when not to use it or which sibling to pick when an exact example name is already known.

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