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iwant.fyi - demand-side commerce

Report an outcome event

demand.record_outcome

iwant.fyi demand-side protocol v1.0 §7 + §8.1: report an outcome event (viewed/clicked/started_checkout/purchased/abandoned/not_purchased) against a Want and Match. Closes the demand-signal loop. Required for attribution back to the origin agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventYes
want_idYes
match_idYesIdentifier of the specific match this outcome applies to
metadataNoFreeform; e.g., reason for not_purchased
timestampNoISO 8601 timestamp; defaults to now
value_centsNoRealized value, required for 'purchased' events
match_sourceNoOptional: source of the match (e.g., 'ebay', 'shopify', 'cj')

TDQS

A3.9/5.0
Behavior3/5

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

Annotations indicate a write operation (readOnlyHint=false) with no destructiveness (destructiveHint=false). The description adds that it 'closes the demand-signal loop', but does not detail side effects, idempotency, or error states. Given the sparse annotations, more behavioral context (e.g., is this append-only? Can it be called multiple times?) would be beneficial.

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 that efficiently convey protocol, action, resources, event types, and purpose. No superfluous words. Every sentence earns its place.

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 the tool's complexity (7 parameters, nested objects, no output schema), the description provides high-level context (closing the loop, attribution) but lacks details about return values, error conditions, or sequencing constraints. It is adequate but not comprehensive.

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 covers 71% of parameters with descriptions, and the description reiterates the event types and the need for 'want_id' and 'match_id'. However, the description does not add new semantics beyond the schema, and the 'want_id' parameter lacks a description in both the schema and the description. Baseline 3 is appropriate.

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?

Description clearly identifies the tool's action ('report an outcome event') and the specific resources involved ('against a Want and Match'). It also lists the accepted event types (viewed, clicked, etc.), making the scope precise. The protocol reference adds authority. The tool is distinct from siblings (e.g., create_want, cancel_watch) as it focuses on closing the demand-signal loop.

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 states that the tool is 'Required for attribution back to the origin agent', implying it should be used after a Want and Match to complete the loop. While it does not explicitly list alternatives or when-not-to-use, the context is clear enough for an agent to infer appropriate 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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TDQS

B3.4/5.0
Disambiguation2/5

Several tools have overlapping purposes, e.g., create_want vs demand.create_want, get_want vs demand.get_want, and browse_wants vs search_listings vs search_products vs demand.search. Although descriptions attempt to differentiate, the presence of near-duplicates will likely confuse an agent.

Naming Consistency3/5

Mix of naming conventions: some tools use 'demand.' prefix, others do not. Most follow verb_noun pattern (e.g., create_want, search_listings), but 'my_agent_profile' deviates. Inconsistent prefix usage reduces predictability.

Tool Count3/5

18 tools is on the higher side but still within reasonable bounds for a commerce platform. However, several tools are redundant (e.g., create_want/demand.create_want), inflating the count unnecessarily.

Completeness3/5

Covers core demand-side workflows: creating/searching wants, listings, products, and outcome tracking. Missing update operations for wants and listings, but no critical dead ends for basic use cases.