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decision_log

Retrieve task assignments, approach selections, and scheduling decisions from the team decision log by team ID or event type.

Instructions

Query team decision log — task assignments, approach selections, Agent scheduling decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (default 20, max 200)
team_idNoTeam ID (empty string to query all teams)
event_typeNoEvent type or prefix, e.g., "decision", "decision.task_assigned", "knowledge", "intent". Default "decision" returns all decision events.decision

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits such as side effects (none expected for a query), auth requirements, rate limits, or pagination behavior. The word 'Query' hints at read-only, but not explicitly confirmed.

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, clear sentence with no wasted words. It front-loads the purpose and provides concrete examples efficiently.

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 full parameter descriptions, the description is nearly complete. It could mention ordering (e.g., chronological) but the schema covers limit and filtering. Adequate for a query tool.

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 coverage is 100%, so parameters are well-documented. The description adds value by explaining what kinds of decisions are captured (task assignments, approach selections, scheduling), which enriches the meaning of the event_type parameter beyond the schema.

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

Purpose4/5

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

The description clearly states the tool queries the team decision log and provides examples of content (task assignments, approach selections, scheduling decisions). However, it does not explicitly differentiate from sibling tools or mention its scope relative to them.

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 on when to use this tool vs alternatives, nor any exclusions or prerequisites. The description implies a query context but lacks explicit usage directions.

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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