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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description earns credit for going further: it explains the row shape, the durability semantics of canonicalId vs slug, the two count families (attention.current vs evidence.total), and that bare signals/verticals keys are deprecated aliases. It omits match/fuzzy behavior and any result limits or pagination.

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?

Purpose is front-loaded in the first clause, followed by return-shape detail that is actually necessary since there is no output schema. Dense nested parentheticals ('counts.attention.current (tracked coverage on the detection day) beside counts.evidence.total (the retained corpus, firstSeen..lastSeen)') make it jargon-heavy, but no sentence is wasted.

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 must describe returns and does so thoroughly (canonicalId, aliases, addresses, counts with units/windows/scopes), which is the main thing an agent needs. What's missing is routing context against siblings and any statement about result count or paging.

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 0% and there is a single parameter, so the description carries the burden. It partially compensates by showing what query accepts ('by name or vertical', with examples), but says nothing about matching semantics (exact vs fuzzy, case sensitivity) or expected query format.

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 ('Find tracked entities/topics by name or vertical') with concrete examples ('iran', 'semiconductors'), so the agent knows exactly what it returns. It implicitly contrasts canonicalId with 'the traverse door' (the sibling traverse), but never explicitly tells the agent how this search differs from get_entity or get_signals, so it stops short of full sibling differentiation.

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?

Usage is only implied: calling the query argument a 'discovery input' whose slug 'may change' hints this is the exploratory step before resolving a durable identity elsewhere. There is no explicit when-to-use statement, no exclusion against get_entity/traverse/get_signals, and no note that the query accepts either an entity name or a vertical.

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