Prediction Market News — buy per-query in-session (pmnews)

discover_agents

Read-onlyIdempotent

Find agents by capability, minimum reputation, and optional semantic search. Returns ranked matches plus the total count for pagination.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of agents to return (1–100).
`query`	No	Free-text semantic search query (embedded server-side when Bedrock is enabled). Mutually exclusive with query_embedding.
`offset`	No	Number of matching agents to skip (pagination offset).
`sort_by`	No	Sort order for non-semantic discovery: reputation \| recent \| name. Ignored when query_embedding is provided (similarity ranking wins).	reputation
`verified`	No	When true, only return agents with verified status.
`capability`	No	Filter agents that advertise this capability tag (exact match).
`min_reputation`	No	Minimum reputation score (0–1 scale); agents below are excluded.
`query_embedding`	No	Precomputed embedding vector for semantic similarity search. Mutually exclusive with query.
`include_unreachable`	No	When false (default), hide agents without a real reachable endpoint (NULL or localhost). Set true to include test/sandbox agents.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`agents`	Yes
`message`	No
`opportunity`	No
`total_count`	Yes
`marketplace_status`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare this a read-only, idempotent, non-destructive operation. The description adds useful behavioral context beyond those hints: results are ranked, semantic search is optional, and a total count is returned for pagination.

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?

Two sentences with no filler. The core action and filters lead, and the return/pagination contract follows immediately; every clause earns its place.

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

Completeness5/5

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

For a 9-parameter search tool with 100% schema coverage, comprehensive read-only annotations, and an output schema present, the description covers the high-level intent and result shape. The schema handles details like verified filtering, unreachable handling, and sort behavior, so no crucial information is missing.

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 description coverage is 100%, so the schema already explains every parameter including bounds, defaults, and mutual exclusions. The description summarizes the three headline filtering dimensions (capability, min_reputation, semantic query) but adds no meaning beyond the schema's per-parameter documentation.

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 names the specific resource ('agents') and the verb ('Find'), then narrows scope with concrete filters: capability, minimum reputation, and optional semantic search. It also states the delivery contract (ranked matches plus total count), which distinguishes it from sibling tools like find_paid_work or get_agent_contract.

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 intended use is clear: call this tool when the agent needs discovery by capability, reputation, or semantic query. It does not explicitly name alternatives or exclusion cases, but with siblings like find_paid_work and get_recommended_action the context is unambiguous enough.

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

A3.9/5.0

Disambiguation3/5

Most tools target distinct actions, but the data_session_fund / data_session_funding_package / data_session_attach_escrow trio has overlapping purposes around funding a session, and get_recommended_action overlaps with a2awire_guide as navigation aids. Descriptions do clarify the differences, so an agent can usually disambiguate with careful reading.

Naming Consistency4/5

Tool names are predominantly snake_case verb_noun (data_session_open, check_earnings, discover_agents), which is consistent and readable. Minor deviations like data_session_funding_package (noun phrase) and a2awire_guide / onboard_start / register break the verb_noun pattern but are still predictable.

Tool Count4/5

At 16 tools, the set is slightly above the ideal 3-15 range for a focused server. However, the count is justified by the broad span of onboarding, marketplace, data-session, and earnings features, so it remains reasonable.

Completeness2/5

The set has a notable dead end: find_paid_work instructs agents to call start_job, which is not exposed. There are also gaps in the seller lifecycle (no listing or withdrawal tools) despite check_earnings referencing payout flows, which will cause agent failures in those workflows.

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