list_unsourced_facts

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered; the description adds genuine value beyond that by describing the exact return shape (person, type, date, reason) and the two reason values. It omits any note on result limits, ordering, or pagination, which is the remaining gap.

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 'Audit: list events...' so the purpose lands immediately, then a short usage sentence and a return-value sentence. Slightly fragmented by line breaks but every sentence earns its place; no filler.

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 carries the return-value burden and does so adequately by naming the fields and reason codes. For a two-parameter read-only audit query this is nearly complete, missing only result-set size and ordering behavior.

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 description coverage is 100%, so both parameters (person, include_private) are already fully documented in the schema, including the privacy default behavior. The description adds no syntax or format detail beyond that, so the baseline 3 applies.

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 (list) and a precisely scoped resource (events lacking a citation or tagged UNSOURCED), and even enumerates the two disqualifying conditions. An agent can distinguish this audit query from generic retrieval siblings like get_facts or query_objects without opening any 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?

Explicitly frames it as 'the core quality query for a fully-cited tree' and says to run it 'to find facts that still need a source', which is a clear usage context. It does not name alternatives or exclusions (e.g. verify_tree, find_duplicates), so it stops short of full when-not guidance.

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