live_cohort_bias_history

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

With no annotations provided, the description carries the full burden. It clearly states the output format ('hourly net-bias snapshots') and flexibility ('each tier or specific tier'). No contradictions exist, but it could detail response structure more (e.g., fields included).

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 concise sentences: purpose, usage examples, output specification. No wasted words, front-loaded with core action. Highly efficient.

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 5 parameters (including a boolean for format) and no output schema, the description gives a high-level goal but lacks detail on return structure (e.g., 'toon format' is only in schema). Could be more complete with a brief output example.

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 description does not need to repeat parameter details. It does not add significant meaning beyond the schema—e.g., does not explain 'bias' calculation or toon format. Baseline 3 is appropriate.

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 it retrieves historical cohort bias data for a specific coin, with example queries that illustrate the tool's purpose. It uses specific verbs ('Get') and resource ('historical cohort bias data'), distinguishing it from related tools like 'live_cohort_bias' which likely provides current data.

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 usage examples ('Use this when a user asks...'), giving clear context for when to invoke the tool. However, it does not mention when NOT to use it or explicitly compare to siblings like 'pulse_cohort_bias_history', leaving some ambiguity.

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