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

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds meaningful behavioral context: it returns exact service IDs, categories, key requirements, and permissions, and emphasizes the 'LIVE catalog' and 'never guess a service id'. This enriches the agent's understanding of what the tool does beyond the annotation. No contradictions found.

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 detailed but not bloated; each sentence serves a purpose, and the main purpose is front-loaded. It includes examples and usage notes, which are useful. It could be trimmed slightly (e.g., the long parenthetical list), but overall it is well-structured and scannable.

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?

With no output schema, the description effectively explains the return contents (service_id, category, key need, permissions) and how to apply them (use verbatim in config.py). It covers both parameters' behavior and clearly sets expectations. For a read-only listing tool, this is comprehensive and leaves no major gaps for an agent to call it correctly.

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 description coverage is 100% with clear descriptions for both parameters. The description reinforces the effect of service_id ('Pass service_id for one service's config fields') and clarifies the category filter is optional. While this adds a little nuance, it does not significantly exceed what the schema already provides, so a baseline 3 is appropriate.

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 clearly states a specific verb ('List') and resource ('platform's available services/integrations from the LIVE catalog'), with concrete examples. It distinguishes itself from siblings by explicitly saying 'Descriptive — what EXISTS, never what to use', which sets it apart from recommendation or configuration tools. The purpose is unambiguous.

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?

It specifies when to use the tool ('so the intake's question is accurate') and what not to do ('never what to use'), which is a clear exclusion. It also gives guidance on the optional service_id parameter ('Pass service_id for one service's config fields'). However, it does not explicitly name an alternative tool (e.g., build_recommend_integrations) for the 'what to use' scenario, though the exclusion is strong.

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