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justhandled_qualified_demand_ledger

Eliminate vanity metrics by classifying normalized commercial events into exposure, operations, candidate signals, qualified demand, validated value, external revenue, or retention.

Instructions

Classify normalized commercial events as exposure, operations, candidate signals, qualified demand, validated value, external revenue, or retention without inflating vanity activity. Costs $0.25 USDC on Base mainnet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventsYes
windowYes
observed_atYes
Behavior3/5

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

With no annotations and no output schema, the description carries the full burden. It discloses a meaningful side effect ('Costs $0.25 USDC on Base mainnet') and communicates a behavioral guardrail ('without inflating vanity activity'). However, it does not disclose whether the tool persists data, returns classifications, or requires authentication.

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 two sentences and front-loads the core purpose before the cost note. There is no filler or repetition; every clause adds information.

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?

Despite a complex nested schema and no output schema, the description does not explain return values, persistence behavior, or event classification semantics beyond the category names. The cost and anti-vanity guardrail are useful, but the tool's overall operational context is under-specified.

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 provides no information about the three top-level parameters (observed_at, window, events) or the nested event fields. The schema's enums and required fields are left entirely for the agent to infer.

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 uses the specific verb 'Classify' and identifies the resource as 'normalized commercial events,' listing the target categories (exposure, operations, candidate signals, etc.). This clearly distinguishes it from the sibling preflight/audit tools, which focus on validation checks rather than event classification.

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?

There is no explicit guidance about when to use this tool versus alternatives, nor any exclusions or prerequisites. The category list implies it is for classifying commercial events, but the description does not state a preferred use case or reference sibling tools.

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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