query_trail_heat

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

Annotations already cover readOnly, idempotent, openWorld and non-destructive, so the safety profile is settled. The description adds genuine value beyond that by disclosing data provenance ('catalog-editorial-v2', discovery_snapshot contract), the presence of campaign evidence, and critically that source freshness is unknown — a real caveat an agent should factor in. It doesn't cover result size or latency, but the disclosure of unknown freshness is substantive.

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 core sentences are dense and front-load the key distinction before the routing hint. The bracketed preamble ('tier: scout_preview_pioneer_full; authority: /api/v1/agent/status') is internal plumbing that doesn't help an agent decide or invoke, which is the main thing keeping this from 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 10-param read-only query with full schema coverage and rich annotations, the description supplies the missing pieces: what the scores actually are, their contract/version, and the freshness caveat. With no output schema, it could say more about the returned record shape, but the contract name and sibling pointer give 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 description coverage is 100% and all 10 params carry inline descriptions including defaults and enum values, so the schema does the heavy lifting. The description adds only the aggregate 'filter/sort/paginate' framing and no per-parameter semantics beyond what's already structured. 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 and resource: filter/sort/paginate the catalog editorial heuristic scores. It explicitly disambiguates from the canonical sibling by saying 'NOT canonical Trail Heat' and naming get_trail_heat. The only drag is that 'catalog editorial heuristic scores' is jargon-heavy, but an agent can still tell the two heat tools apart.

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?

Names the alternative explicitly ('For quantitative DeFiLlama-backed scores use get_trail_heat') with the exact condition that selects it. This is the same routing pattern as the high-scoring calibration example, and nothing about when to reach for this versus get_trail_heat 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.