record_prediction

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

With no annotations, the description carries full disclosure burden. It highlights immutability ('immutable pre-earnings forecast') and format constraints. However, it does not mention idempotency, error behavior, side effects, or rate limits. Sufficient but not exhaustive.

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 three sentences, front-loaded with the core purpose. Every sentence adds necessary constraints or definitions. No wasted words.

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?

Given 13 parameters, 0% schema description coverage, and an output schema that is not described, the description leaves many gaps. It explains only a subset of parameters and does not cover return values, error conditions, or prerequisite checks for a complex recording tool.

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 0%, so description must compensate. It explains semantics for expected_earnings_at (ISO 8601 with timezone), financial fields (same currency), and post_earnings_close. However, 8 of 13 parameters (e.g., ticker, fiscal_period, harness, model, thinking_setting, notes, currency) remain unexplained. Adds value for some but not all.

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 states 'Record one immutable pre-earnings forecast.' This is a specific verb (record) and resource (immutable pre-earnings forecast). It distinguishes from siblings 'get_results' (reads) and 'record_actuals' (records actuals), so an AI agent can tell when to use this tool.

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 provides explicit constraints: ISO 8601 timestamp with timezone, same reporting currency for financial fields, and definition of post_earnings_close. It implies use for pre-earnings forecasts but does not explicitly state when not to use or compare to siblings. Still clear context.

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