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record_execution

Idempotent

Record user action on a committee verdict: mark as executed or declined with a reason, updating the execution ledger.

Instructions

Record whether the user executed or declined a committee verdict, with their reason. Appends to the execution ledger; idempotent — replaying the same record is a no-op, so retries are safe.

Call when the user says "I bought it / I didn't buy / I disagree". When they decline, ask one short question for the reason first — this closes the adoption-rate loop that decisions reports on.

Args: decision_id: "/" from the decisions output. executed: True if the user acted on the verdict, False if declined. reason: The user's stated reason (especially when declined). trade_ids: Optional trade record IDs to link explicitly.

Returns: The stored execution record, or {"status": "error", "error": ...}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoThe user's stated reason (especially when declined).
executedYesTrue if the user acted on the verdict, False if they declined.
trade_idsNoOptional trade record IDs to link explicitly.
decision_idYes"<date>/<symbol>" from the decisions tool output.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description complements the annotations by explaining the idempotent behavior: 'replay the same record is a no-op, so retries are safe'. It also notes that the tool appends to the execution ledger and returns the stored record or error, providing full behavioral disclosure beyond the annotations' flags.

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?

The description is concise and well-structured: first sentence states purpose, then behavioral note, usage guidance, Args, and Returns. Every sentence serves a purpose, and the structure is easy to parse. No unnecessary words.

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

Completeness5/5

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

Given the tool has 4 parameters (2 required), an output schema, and annotations, the description covers all necessary context: purpose, when to call, how to handle edge cases (decline), parameter details, and return value format. It is complete for effective agent use.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the format of `decision_id` ("<date>/<symbol>") and the context for `reason` (especially when declined). While the Args section is somewhat redundant with the schema, it provides a clear, contextual listing that helps the agent understand parameter relationships.

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 explicitly states the verb 'Record' and the resource 'execution of committee verdict'. It distinguishes itself by specifying the scope (whether the user executed or declined) and mentions idempotency and retry safety, which are unique traits among siblings.

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

Usage Guidelines5/5

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

The description provides explicit when-to-call scenarios: 'when the user says "I bought it / I didn't buy / I disagree"'. It also gives specific guidance for the decline case: ask one short question for the reason first, referencing the sibling tool `decisions` and the adoption-rate loop.

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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