briefing_stock_history_get

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

With no annotations provided, the description carries the full burden and covers data_status semantics, required follow-up actions for incomplete snapshots, and strict output tone constraints (no predictions, no judgement words). It makes the tool's non-obvious behavior explicit.

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 long but appropriately structured with a purpose-first opening, example triggers, a bulleted data-status contract, and a clear section on tone constraints. Every segment adds necessary operational detail.

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 no output schema, the description explains all key return values and behavior, including the raw_only/missing recovery workflow, so an agent can invoke the tool and handle incomplete data correctly. The only minor gap is the exact shape of the divergence detection result, but the workflow is sufficiently complete.

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%, so the schema already defines ticker, days, and token. The description only maps '最近一周' to the days parameter and does not add materially new syntax or format details beyond the schema.

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 opens with a specific verb+resource phrase '查看某只股票的历史情绪趋势' and specifies the returned data (daily sentiment score, close price, change, divergence detection). It provides user trigger examples, which clearly differentiates this historical trend view from sibling tools like stock_digest or history_record.

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?

It explicitly defines when to call (user asks 'AAPL 最近一周情况怎么样', etc.) and includes a conditional workflow for raw_only/missing data that names the exact alternative tools to invoke (briefing_stock_digest and briefing_stock_history_record). This is strong when-to-use guidance with concrete alternatives.

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