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

Annotations already cover safety (readOnly, idempotent, closed-world), but the description adds substantive meaning: the Beta(2,2) prior starting at 0.50, how scores shift on re-checks, and what LB10 and 'resolved tips' mean. It does not disclose result ordering or count limits, which keeps it below a 5.

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 usage trigger is front-loaded, the field list follows, and the prior explanation is compact. The Bayesian-prior sentence is dense but earns its place by making the trust score interpretable; nothing is redundant.

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 one optional parameter and no output schema, the description carries the burden of explaining return fields and does so (tier, trust score, LB10, resolved tips count). Minor gaps remain around ordering and result volume, but an agent has enough to call it correctly.

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 100% and the schema already explains that the name filter is optional and may match multiple sources. The description's single line 'Optionally filter by name' adds nothing beyond that, so baseline 3 is appropriate.

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?

Specific verb ('Lists') plus resource ('the sources Context Pill reads') and the exact fields returned (tier, trust score posterior mean, LB10, resolved tips). It does not explicitly differentiate itself from get_latest or search_claims, so it falls short of a 5 despite a very clear statement of what it does.

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?

Gives an explicit trigger: use when the user asks how far to trust a source behind an AI claim, or when weighing a vendor claim. There is no mention of when not to use it or which sibling (get_latest, search_claims) handles adjacent needs, so routing to alternatives is left to inference.

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