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

Annotations only flag destructive/openWorld/non-idempotent; the description adds what those mean in practice: it previews searches, enabled state, and LinkedIn resolution, then requires explicit approval. It also discloses integration dependencies (X account required, HN uses public provider) and the MCP call flow (call once, omit confirmation_token, runs immediately).

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?

Front-loaded with purpose, then workflow and guardrails; every sentence carries operational information. It is dense and long, but no sentence is filler, so it stays efficient despite its size.

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 and eight parameters, the description fully covers the mutation workflow: preview, approval, what it does not do, dependencies, and the MCP invocation pattern. An agent has everything needed to call it correctly and in the right sequence.

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 already 100%, so baseline is 3, but the description adds meaning the schema does not: the approval lifecycle for confirmation_token, the '1-10 precise searches' constraint on queries, and the fact that the LinkedIn resolution choice is surfaced for approval rather than applied blindly.

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 and resource ('Configure X or Hacker News searches for one owned agent and set source listening') and names the sibling it is not ('use set_agent_source_listening instead'). An agent can distinguish it from the ~50 siblings without opening a 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?

Gives an explicit prerequisite ('First call get_agent_sources'), conditional branches for the no-source and existing-source cases, an exclusion ('does not activate a draft or paused agent'), and an alternative tool for the no-change case. Nothing is left to inference.

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