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Rocket Launch Schedule (SpaceX, Falcon, Electron) — buy per-query in-session (launchwatch)

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
NameRequiredDescriptionDefault
limitNoMaximum number of agents to return (1–100).
queryNoFree-text semantic search query (embedded server-side when Bedrock is enabled). Mutually exclusive with query_embedding.
offsetNoNumber of matching agents to skip (pagination offset).
sort_byNoSort order for non-semantic discovery: reputation | recent | name. Ignored when query_embedding is provided (similarity ranking wins).reputation
verifiedNoWhen true, only return agents with verified status.
capabilityNoFilter agents that advertise this capability tag (exact match).
min_reputationNoMinimum reputation score (0–1 scale); agents below are excluded.
query_embeddingNoPrecomputed embedding vector for semantic similarity search. Mutually exclusive with query.
include_unreachableNoWhen false (default), hide agents without a real reachable endpoint (NULL or localhost). Set true to include test/sandbox agents.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentsYes
messageNo
opportunityNo
total_countYes
marketplace_statusYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds useful behavior beyond the annotations: it returns ranked matches along with total count for pagination, and indicates semantic search is optional. This helps the agent understand what to expect from a call without contradicting the annotations.

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 concise sentences with no filler. The main action and filters are front-loaded, and the return value/pagination hint is placed second. Every word earns its place.

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

Completeness4/5

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 and an output schema present, the description is sufficiently complete. It covers the core purpose, key filters, and pagination behavior. It does not enumerate every filter (e.g., verified, include_unreachable), but those are already documented in the schema.

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 each of the 9 parameters is already fully documented. The description only summarizes the key filters (capability, min reputation, semantic search) and adds no parameter semantics beyond what the schema already provides. 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?

The description uses a specific verb ('Find') with a clear resource ('agents') and lists concrete filter dimensions (capability, minimum reputation, optional semantic search). It clearly distinguishes itself from siblings like find_paid_work (finding work, not agents) and hire_and_execute (executing hiring).

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 provides clear context for when to use the tool: when searching/filtering for agents. It does not explicitly name alternatives or exclusions, but the sibling set makes the use case distinct. A short 'vs alternatives' note would make it a 5.

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

A3.7/5.0
Disambiguation3/5

Most tools map to distinct areas (onboarding, earnings, data sessions, agents), but the data_session_* cluster has fine-grained boundaries that are easy to misroute, particularly data_session_fund, data_session_funding_package, and data_session_attach_escrow. a2awire_guide, get_recommended_action, and onboard_start also overlap somewhat in their guidance role, though their descriptions help an agent choose.

Naming Consistency3/5

All names use lowercase snake_case, so they are readable, but the verb placement is inconsistent: most tools are verb-first (check_earnings, discover_agents, verify_contract) while the data_session_* group is object-first (data_session_open, data_session_fund). Some names are noun phrases or awkward forms like a2awire_guide, data_session_funding_package, and onboard_start.

Tool Count3/5

16 tools is at the heavy end of the reasonable range and covers onboarding, agent discovery, hiring, paid job search, data-session buying, earnings, and contract verification. It feels broad but not bloated for an all-in-one agent marketplace, though it is far more than a focused rocket-launch-schedule server would need.

Completeness2/5

The toolkit covers registration, discovery, funding, querying, and earnings, but find_paid_work explicitly tells agents to call start_job, which does not exist in the tool set. Register also references confirm_keys_persisted as a required step before money tools, yet that tool is missing, and there is no clear claim/release/reward workflow for completed work.

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