demand.list_verticalsiwant.fyi demand-side protocol v1.0 §8.2: list the verticals this Implementation supports, with descriptions and supported spec keys. Useful for agent capability discovery.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's job is lighter. It adds a protocol reference but no further behavioral details like rate limits or auth, which is acceptable given the simple read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences: one states purpose, the other provides usage context. No wasted words, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter discovery tool with no output schema, the description adequately indicates what the response contains, making it complete for an agent to understand and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, baseline is 4. The description adds value by specifying output contents (descriptions and supported spec keys), which is beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists supported verticals with descriptions and spec keys, distinguishing it from sibling list tools like demand.list_constraints and demand.list_watches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates it is useful for agent capability discovery, providing a clear use case. However, it does not explicitly state when not to use it or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.