list_endpoints

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions that it lists endpoints 'across all loaded .mind files' and 'surfaces environment names', which adds scope and output context. However, it does not describe return structure, error behavior, or any side effects (though likely a safe read-only operation). This is adequate but not rich.

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?

The description is three concise sentences, front-loaded with the main purpose, followed by usage guidance and a clear trigger. Every sentence contributes useful information with no redundancy or fluff.

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?

For a simple tool with one optional parameter and no output schema, the description covers the core aspects: what it does, when to use it, and what the filter does. It does not detail the return value structure, but the high-level output hints ('Lists all available endpoints', 'surfaces environment names') are adequate for a discovery tool. Minor gap: no explicit mention of limits or pagination, but not critical.

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 schema already provides 100% coverage for the 'filter' parameter, describing it as a substring match on method, path, or section. The description repeats this in prose ('Filter by method, path, or section') without adding new meaning. Thus, the schema does the heavy lifting, and the description adds marginal value.

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?

The description explicitly states 'Lists all available endpoints across all loaded .mind files' and 'surfaces the available environment names', giving a specific verb, resource, and scope. This clearly distinguishes it from sibling tools like list_apis (which likely lists APIs at a higher level) and get_endpoint_schema (which fetches a single schema).

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 description provides clear usage context: 'Use this to discover what endpoints exist across all APIs' and 'Call this when the user references an API or asks what's available.' It stops short of explicitly naming alternatives or listing when-not-to-use scenarios, but the guidance is sufficient for typical discovery purposes.

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