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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context by disclosing the derivation model (FACT/DERIVED/UNKNOWN) and that lineage and evidence ids are surfaced, but says nothing about auth needs, rate limits, or failure modes.

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 opening rhetorical question is front-loaded and effective, but the middle sentence is a dense enumeration of return fields that largely duplicates what the existing output schema already provides, so not every clause earns its place.

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 an output schema present, the description need not restate return values, and it correctly focuses on purpose, the discovery mode, and the fact/source dependency. What remains missing is differentiation from sibling lookup tools, which matters given seven related tools.

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?

Beyond the schema (67% coverage), the description explains the cross-parameter dependency that the schema cannot express: 'fact' may be omitted to enumerate explainable facts, and 'source' is only meaningful with fact=source.counted. It does not annotate each enum member individually, but the conditional logic is genuinely additive.

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 states a specific verb and resource: it explains the facts behind HEY's claims (why a project is 'Shipping', 'Dormant' or 'Still Building', or why a figure is shown), and names the returned concepts (value, rule, version, source, lineage, evidence ids). This is concrete and distinguishable from generic read tools, though it never explicitly contrasts itself with siblings like get_evidence or get_contract.

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 gives one real usage rule — 'Omit fact to list what can be explained' — which tells the agent how to enter discovery mode. However, it offers no guidance on when to choose this tool over the many siblings (get_evidence, get_contract, research_answer), leaving the selection decision to inference.

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