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Glama

confirm_decision

Finalize decisions by recording rationale and routing human approval for irreversible actions, preventing risky AI assumptions.

Instructions

Record a finalized decision. Irreversible decisions always require human approval. Always pass project_root as the current working directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNogeneral
decisionYes
rationaleYes
project_rootNo.
is_irreversibleNo
alternatives_consideredNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses an important behavioral constraint—irreversible decisions require human approval—and the project_root requirement. It does not explain what happens when approval is missing, whether the record is persisted, or what the response is, so transparency is partial.

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 sentences with no filler: the first states the primary purpose, and the second packs two critical usage constraints. The structure front-loads the main action and keeps necessary operational details compact.

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

Completeness3/5

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

Given six parameters and no annotations or output schema, the description covers the most decision-relevant behaviors but leaves gaps. It does not describe the approval workflow, the persistence or result of recording, or how this tool relates to ask_human and revoke_decision, so an agent still has to infer part of the invocation context.

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?

The description adds meaning to project_root ('current working directory') and is_irreversible ('requires human approval'), which the bare schema does not convey. However, it does not clarify category, alternatives_considered, or the required decision and rationale fields beyond their names.

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 states a specific action ('Record') and a specific object ('a finalized decision'), making the tool's core purpose clear. It is distinguishable from siblings like query_decisions and revoke_decision, though it does not explicitly name them or contrast with them.

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

Usage Guidelines3/5

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

The description provides useful situational guidance: irreversible decisions require human approval, and project_root must be passed as the current working directory. However, it does not explicitly state when to choose this tool over query_decisions, revoke_decision, or ask_human, leaving the selection partly implied.

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