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agent-discovery-index

Where AI agents discover products, and how to be listed there with measured results (Agent Ads). 7-day trial, founding $50/mo (first 10, 12 mo) then $100/mo. Follow start_here.hop first (302). Task text discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check
websiteNoPublic https website (homepage domain) to check for agent readiness: robots.txt, llms.txt, sitemap.xml, extractable HTML. Bounded, identified, robots-respecting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.1/5.0
Behavior2/5

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

The only behavioral disclosures are 'Task text discarded' and 'Follow start_here.hop first (302).' With no annotations, the description leaves side effects, data access, and return behavior completely unexplained. Pricing and trial details do not help an agent understand what happens when it calls the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short but under-specified: the front-loaded sentence is a vague noun phrase, the pricing sentence is irrelevant to invocation, and 'Follow start_here.hop first' is unexplained. It is not efficiently concise; it wastes its few sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 10-parameter tool with no output schema and no annotations, the description is severely incomplete. It does not state the tool's action, expected result, or when it applies, leaving an agent unable to select or interpret it. The only concrete instruction, 'Follow start_here.hop first', is unexplained.

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?

Schema coverage is 100%, so the baseline is 3 even without parameter details in the description. The overview adds no parameter-level meaning beyond what the schema already provides, and its mention of discarded task text is only marginally useful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description reads as marketing copy for a product listing, not a tool action. It says 'Where AI agents discover products' but never states what invoking this tool does, and the name is not enough to distinguish it from agent-ads-index or agent-tool-index.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to call this tool versus its siblings. 'Follow start_here.hop first' is an opaque instruction, not a decision rule or exclusion. The description offers no clear condition for use.

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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