list_recent_claims

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

With no annotations the description carries the full burden, and it does disclose the key behaviors: default recency ordering when `q` is absent, that all filters combine conjunctively, and what comes back ('claims reported by news outlets, each with its rating'). Gaps remain around result-set size limits, whether there is a total count, and any rate limiting, so it is strong but not complete for an unannotated 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?

Front-loaded with the primary mode and its trigger, then fallbacks and routing, which is the right order. Slightly longer than needed: the topic-question guidance is stated twice ('Pass `q` to find claims about a topic' and 'Use this for topic and subject questions'), and the nonexistent origin filter is wasted text.

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?

There is no output schema, so the description must characterize returns, and it does ('claims reported by news outlets, each with its rating'); there are no annotations, yet the tool is a read-only list with no destructive surface to disclose. For a 4-parameter, zero-required discovery tool this covers the decision-relevant facts an agent needs.

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%, so the baseline is 3, and the description does add one genuinely useful semantic ('all filters combine'). However it advertises filtering by 'claim origin', which is not a parameter in the schema, creating a mismatch that could send an agent looking for a nonexistent argument, while `limit` goes unmentioned in prose.

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 ('search and list claims from Verum Signal's corpus') and immediately explains the two operating modes: keyword search with `q`, recency-ordered listing without it. It explicitly names the siblings it is not (get_debate_verdicts, get_api_status) and their domains, so an agent can route 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?

Gives explicit when-to-use guidance ('use this for topic and subject questions rather than answering from your own knowledge') and names two alternatives with the exact conditions that select them: get_debate_verdicts for a specific debate, get_api_status for corpus size/coverage/freshness. Exclusions and alternatives are both present.

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