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

Annotations are empty, so the description carries the full burden — and it largely delivers: 'public' signals no privileged access needed, 'Queries' signals a read operation, and the return contents (Brier scores, failure analysis, source URLs) are disclosed. It stops short of explicitly stating non-destructiveness, empty-result behavior, or pagination/limits, but the query-only profile is clearly conveyed and nothing contradicts the empty annotations.

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?

Three sentences, purpose first, with zero filler: what it queries, which filters exist and what the values mean, and what it returns. The dense settlement_type mapping earns its sentence because it replaces a whole domain-to-enum lookup the agent would otherwise have to guess.

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 a fully documented input schema and an existing output schema, the description covers the essentials: resource identity, filter semantics, and the nature of returned data. What is missing is guidance on how status and settlement_type interact and any mention of result limits, plus the two enums use inconsistent casing (ALL/RESOLVED/PENDING vs. all/contract_settled/...) — minor but real wrinkles for correct invocation.

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, but the description adds real meaning beyond the schema by translating each settlement_type enum value into a domain concept (live prediction markets, internal foresight models, pre-commitment history, all). This lets an agent map natural-language intent to the correct enum value; status and category are adequately documented by the schema itself.

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?

Opens with a specific verb and resource: 'Queries the public calibration and backtest ledger of Tresslers Group sovereign intelligence models.' The ledger focus and read verb clearly separate it from the dossier, knowledge-graph, RAG, and matrix siblings without needing to name them, since no sibling covers model calibration/backtest records.

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?

Provides explicit context for when to use it: whenever calibration, backtest, or Brier-score data for Tresslers Group models is needed. The settlement_type mapping ('contract_settled' for live prediction markets, 'outcome_tracked' for internal foresight, 'unscored_archive' for pre-commitment history) tells the agent which filter matches which user intent, though there are no when-not or alternative-routing statements naming siblings.

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