explain

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

Given no annotations, the description fully carries the burden of transparency. It accurately states the tool returns structured data with claims, verdicts, evidence snippets, and synthesis. There are no hidden side effects or destructive actions implied, but it could mention if the tool is purely read-only or caches data, which would earn 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 description is concise and well-structured, with no unnecessary words. It uses clear, functional language. However, it could be slightly more structured (e.g., bullet or numbered list), so it does not quite earn a 5.

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 only 2 parameters and no output schema, the description provides thorough context: it explains the return structure (claims, verdicts, evidence snippets, synthesis), how to use the optional filter, and hints at discoverability of dimension values. This is complete and covers the agent's 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%, baseline 3. The description adds value beyond the schema by explaining the purpose of the dimension filter and providing a best practice (run without dimension first). This extra guidance justifies a 4.

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 clearly identifies the tool's purpose: providing structured natural-language explanations of why a Hlido-reviewed agent has its current score, pulling claim-by-claim evidence. It distinguishes the tool from siblings like get_scorecard and verify_claim by focusing on explanation rather than raw scores or verification.

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?

The description gives clear usage context: pass an optional dimension to filter, omit for full picture. It even advises running without dimension first to discover supported_dimensions. However, it does not explicitly state when not to use this tool or mention alternatives, so it lacks direct exclusions.

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