treeflow_list_credentials

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

With no annotations provided, the description carries the full behavioral burden. It clearly indicates a read-only listing operation scoped to the workspace and implies the return content (configured AI providers) and its purpose (checking availability). It does not describe output format, but for a zero-parameter list tool this is acceptable.

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 concise sentence that front-loads the verb and resource, immediately states the scope, gives examples, and ends with the intended use. There is no redundant or filler content.

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 zero-parameter, no-output-schema list tool, the description is largely complete: it names the resource, scope, examples, and purpose. It could optionally mention the exact response shape, but the verb 'Lista' and availability-check purpose make the expected behavior clear enough.

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 has zero parameters, so no parameter-level detail is needed. The description adds context about what is being listed, which compensates for the empty input schema.

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 uses a specific verb ('Lista'), a clear resource ('proveedores de IA configurados en el workspace'), and concrete examples (OpenAI, Gemini, Groq, Twilio, Meta) which distinguish it from siblings like list_integrations and list_users. The stated purpose, 'verificar disponibilidad', further clarifies what the tool accomplishes.

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 'para verificar disponibilidad' gives a clear context for when to use the tool. It does not explicitly mention exclusions or alternatives, but the resource scope is specific enough that an agent can infer when it applies.

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