get_standup

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

No annotations are provided, so the description carries the full burden — and it delivers thoroughly. It declares 'pure read', explicitly states 'NO LLM on the relay side' (observations are hand-rolled heuristics), details the default filtering behavior (non-offline, flippable via include_offline), documents the auth mechanism ('any agent token'), and lists all error codes. This is exemplary disclosure.

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?

Well structured with clear labeled sections: When to use, Behavior, Auth, Returns, Errors. Every sentence earns its place — no filler, each line conveys operational information an agent needs. Front-loaded with the core purpose and usage decision, then behavioral details, then error contract.

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 tool with nested objects, 3 params, no output schema, and no annotations, this description is exhaustive. It defines the complete return structure, ALL error modes, authentication requirements, filtering semantics, and a nuanced behavioral caveat (heuristic observations, no LLM server-side). Nothing material is left ambiguous for correct invocation and result interpretation.

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 100%, so the schema documents all params. The description adds meaningful semantic value on top: it explains the since values, defines what include_offline flips in the default behavior, specifies that agents/roles narrow the snapshot and AND together, and rejects the agent_token parameter since it's noted optional. It adds real context beyond the schema's field descriptions.

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 is highly specific: 'One-shot team-status synthesis for orchestrators' with a clear verb-resource pair (get + standup/rollup). It explicitly defines the return contract (active_agents, message_activity, task_state, observations), distinguishes its server-side aggregation role from sibling tools, and names alternative tools to fall through to. This belongs in the Tier A category.

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?

Excellent when/when-not guidance. It states explicitly to use this instead of chaining discover_agents + get_messages + get_tasks, points out the token-efficiency rationale, and instructs to 'fall through to the underlying tools' for drill-downs. It also enumerates all error types, giving the agent actionable preconditions.

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