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

With no annotations, the description carries the full burden and does so well. It discloses that this is a read, defines the evidenceStatus behavior (receipted rows carry source-attributed evidence URLs; unreceipted rows are labeled leads), and adds the critical interpretation guardrail that the measured association is 'never a directional claim'. It also reveals the 500/day quota.

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 front-loaded with the most actionable information ('START HERE', cheap read) and packs meaningful payload semantics into the middle. The statistical 'Measured property' block is verbose and slightly awkward, but it earns its place as a transparency safeguard, so the overall size is acceptable.

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?

There is no output schema and no annotations, yet the description gives an agent enough to call and interpret the tool: payload parity, output fields, evidenceStatus semantics, quota, and an explicit caveat about the association not being directional. Nothing critical for deciding whether or how to use this read-only feed is missing.

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 input schema has 100% description coverage for both `limit` and `direction`, so the baseline is 3. The description adds no additional meaning for either parameter and does not mention them at all, relying entirely on the schema to define them.

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 identifies a clear resource — the 'full machine-readable signal feed' — and specifies what it contains: every entity flagged by the attention engine, with trajectory, domains, desk membership, and evidenceStatus. It is specific and useful, but it does not explicitly name or contrast sibling tools like get_desk_feed or top_accelerating, so the differentiation is only implicit.

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 gives strong usage guidance: 'START HERE for browsing' and positions the tool as 'the cheap read (500/day, no model work)'. This tells an agent when to reach for it, but it does not state when not to use it or name alternatives for more specific/expensive reads.

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