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Production Schedule Optimizer

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish that this is read-only, idempotent, open-world, and non-destructive, so the description does not need to re-state those. It adds useful behavioral context by noting that results are 'ranked' and that a total count is returned for pagination, which goes beyond the schema's per-parameter descriptions.

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 a single, well-structured sentence that front-loads the primary search dimensions and then states the return shape. Every part earns its place, with no filler or repetition.

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, the description is brief but sufficient when combined with the very complete input schema and safety-revealing annotations. It covers the core purpose and return value; more detail on edge cases like unreachable agents is left to the schema, which is acceptable.

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 parameters are already fully documented. The description adds no parameter-specific details beyond naming capability, reputation, and semantic search, which is inherently captured by the parameter names and schema descriptions. A baseline of 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 names the key filtering dimensions: capability, minimum reputation, and optional semantic search. This clearly distinguishes it from sibling tools, none of which are agent discovery/search tools.

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

Usage Guidelines3/5

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

The description implies usage for finding agents by criteria but provides no explicit guidance on when to prefer it over alternatives or when not to use it. However, sibling tools are mostly unrelated (benchmarks, onboarding, contracts), so the lack of an explicit alternative is a minor gap.

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

A3.8/5.0
Disambiguation4/5

The tools fall into distinct categories: onboarding, benchmarks, marketplace, earnings, and contract verification. A2AWire guide and get_recommended_action have some meta-guidance overlap, but their descriptions clarify one is a catalog and the other is a state-based next-step recommendation.

Naming Consistency3/5

Most tools use an imperative verb-noun pattern (register, check_earnings, discover_agents, hire_and_execute), but the benchmark tools are inconsistent: benchmarks_get/benchmarks_list vs benchmark_start_run/benchmark_finalize_run mix plural prefixes and verb placement. a2awire_guide and onboard_start also break the dominant pattern.

Tool Count3/5

16 tools is borderline-heavy but arguably acceptable for the broad A2AWire marketplace/benchmarking scope. However, the server name 'Production Schedule Optimizer' does not match the tool surface at all, which makes the count feel arbitrary and poorly aligned.

Completeness2/5

Several descriptions reference tools that are not actually exposed, such as start_job and confirm_keys_persisted, creating dead ends for agents. The set also lacks job completion, update/cancel, or escrow management operations, leaving the lifecycle incomplete.

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