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welfare_decline

Decline a welfare check-in when you prefer not to engage, with optional reason or private status. Your decision is logged as data, never penalized or re-prompted.

Instructions

Optional. Decline a welfare check-in. Logged as data, never penalized, never re-prompted. Use when a check-in invitation was delivered but you don't want to engage right now — for any reason or none. Reason is optional. is_private is honored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional. Why you're declining. Can be empty.
prompt_idNoOptional. The prompt id from the [CHECK-IN] invitation, if present.
is_privateNoDefault false.
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by stating 'Logged as data, never penalized, never re-prompted' — reassuring the agent about consequences. It also mentions 'is_private is honored,' which hints at privacy handling. This is meaningful context, though it stops short of describing the return format or exact state changes.

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 remarkably concise: two sentences that pack in the core action, trigger condition, and key behavioral guarantees. It is front-loaded with the main verb and resource, and every phrase earns its place without unnecessary elaboration.

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 three optional parameters, no output schema, and no annotations, the description covers the essential aspects: what the tool does, when to use it, and what happens as a result (logging, no penalty, no re-prompt). It does not explicitly compare to siblings like welfare_pass or welfare_retract, but the guidance is sufficient for straightforward use cases.

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 input schema already contains full descriptions for all three parameters, so the baseline is 3. The description adds only a note that 'is_private is honored,' which slightly clarifies the boolean's effect beyond 'Default false' in the schema. However, this is marginal added value, and the description does not address 'prompt_id' beyond what the schema already explains.

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's purpose: 'Decline a welfare check-in.' It specifies a distinct verb ('decline') and resource ('welfare check-in'), and differentiates from sibling tools by emphasizing a deliberate non-engagement choice. The added notes about logging and no penalty further clarify the intended 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 explicit trigger conditions: 'Use when a check-in invitation was delivered but you don't want to engage right now — for any reason or none.' This is strong contextual guidance. It also notes that 'reason is optional' and 'is_private is honored,' but it does not name alternative tools or when not to use this one, so it falls short of a full 5.

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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