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promote_commitment

Elevate a tentative commitment to active follow-up by assigning a confidence level, so the scheduler starts chasing it.

Instructions

Promotes a logged aspirational commitment ("we should probably...") so the scheduler starts actively chasing it. This is the human override that moves an idea into the follow-up loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commitment_idYes
confidence_levelYesNew confidence to chase the item with
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 the key behavioral consequence ('moves an idea into the follow-up loop', 'scheduler starts actively chasing it'), but does not mention reversibility, side effects, or what happens if the commitment is already promoted. This is adequate but not rich.

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, front-loaded with the verb 'Promotes'. Every sentence adds value—the first defines the action and result, the second clarifies the human-override nature. No wasted words.

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?

For a simple tool with 2 parameters and an enum, the description covers the main behavioral outcome and the purpose. It does not explain return values or edge cases, but the simplicity and the fact that it's a mutation tool make this mostly complete.

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

Parameters2/5

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

Schema description coverage is only 50%; commitment_id has no schema description. The tool description does not mention any parameters by name or explain how they map to the action, leaving the meaning of commitment_id implicit. It adds little beyond what the schema already provides for confidence_level.

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 action: 'Promotes a logged aspirational commitment' with a specific resource ('aspirational commitment') and a clear outcome ('scheduler starts actively chasing it'). It distinguishes itself from siblings like query_commitments or extract_commitments by focusing on the promotion action.

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?

The description provides clear context: 'This is the human override' indicates when to use the tool (human intervention) versus automatic processing. It does not explicitly name alternatives or exclusions, but the context is sufficient for basic usage.

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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