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record_execution

Idempotent

Captures whether a user executed or rejected an investment decision, with optional reason, and appends the record to an immutable audit ledger.

Instructions

记录用户对某决议的执行/拒绝 + 原因(幂等追加账本)。 用户说"我没买/我买了/我不同意"时调用;拒绝时先问一句原因。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNo
executedYes
trade_idsNo
decision_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations declare idempotentHint=true, and the description adds 'idempotent append ledger', reinforcing idempotency. It also mentions asking for reason on rejection, adding behavioral context beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences that front-load the core purpose and usage. No wasted words, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and sibling tools, the description covers the main functionality and when to use it. However, it lacks details on return values, error handling, or prerequisites, but these are somewhat mitigated by the output schema and annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains 'reason' and conditionally 'executed' via usage context, but does not cover 'decision_id' or 'trade_ids'. Parameter names are somewhat self-explanatory, but the description is insufficient for full clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it records user execution or rejection of a decision with a reason. It uses a specific verb ('record') and resource ('execution/rejection of a resolution'), distinguishing it from sibling tools like 'decisions' and 'explain_decision'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells when to call: when the user says 'I didn't buy / I bought / I disagree', and advises asking for a reason on rejection. This provides clear context, though it does not mention when not to use alternatives.

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

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