Grade evidence corroboration for a claim

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 the verdict logic (2+ distinct sources plus a non-textual signal for 'confirmed', disagreement surfacing as 'mixed', null results gated by coverage, thin coverage capping the verdict). It does not describe error behavior or the shape of the returned verdict object, leaving a modest gap for a scoring tool.

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 key constraint ('NOT a vote count') is front-loaded and the grading rules follow in a tight, information-dense sentence. It is longer than average but nearly every clause carries a distinct rule; minor density without wasted sentences.

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 no annotations and no output schema, the description conveys the decision rules an agent needs to invoke it correctly and anticipate verdict semantics. It stops short of stating return-value structure, but the embedded verdict names give sufficient orientation.

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 only 50%, but the description compensates by explaining how the parameters drive outcomes -- distinct `source` counting for independence, non-textual `kind` unlocking 'confirmed', and coverage capping the verdict. This adds real semantic meaning beyond the field-level schema 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?

States a specific verb and resource ('grades confidence in a claim from a set of independent evidence signals') and immediately differentiates itself from a naive alternative with 'NOT a vote count'. An agent can distinguish this from siblings like check_grounding or score_trust_identified without opening the 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 says when to use it: 'whenever several pieces of evidence were gathered for a claim (by you, another tool, or a research/verification pass) and you need an honest, non-inflated verdict'. It gives a clear triggering context but does not name or contrast against specific sibling tools, so it stops short of full routing guidance.

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