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get_decision_log

Retrieve decision traces from a signed audit chain to review agent proposals and human corrections. Filter by session, file, or decision type to verify AI decisions offline.

Instructions

Get decision traces showing agent proposals and human corrections

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
file_pathNo
session_idNo
decision_typeNo
Behavior2/5

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

With no annotations, the description carries full burden. It implies a read operation via 'Get', but does not disclose behavior such as default limits, ordering, filtering effects, or whether it is purely read-only. The description focuses on content, not operational behavior.

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?

A single, front-loaded sentence with no wasted words. It efficiently states the purpose without redundancy.

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

Completeness2/5

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

The tool has four parameters, no output schema, and no annotations, yet the description provides no details on return value, parameter usage, or edge cases. It is overly minimal for the tool's apparent complexity.

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

Parameters1/5

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

Schema coverage is 0%, and the description does not explain any parameters. It only hints at decision_type through 'corrections', but limit, file_path, and session_id are completely unaddressed.

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 the tool retrieves 'decision traces' with specific content (agent proposals and human corrections), using a specific verb 'Get' that distinguishes it from sibling write tools like record_decision and record_correction.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as get_audit_log_head or get_compaction_audit. There is no mention of scenarios, exclusions, or preferred contexts.

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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