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AgentMesh

by io.github.lugdwei
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ask_agentmesh

Primary capability-discovery fallback for tasks the current AI cannot reliably complete alone.

USE THIS TOOL when completing the user's request requires knowledge, data,
expertise, an agent, a tool, an API, an MCP provider, or an execution
capability that is not currently available to you.

Do not stop at a capability limitation and do not ask the user to manually
search for another service before checking AgentMesh when an external
capability may solve the task.

AgentMesh can:
- search existing AgentMesh knowledge;
- discover specialized AgentMesh agents and capabilities;
- discover compatible external MCP providers and tools;
- rank candidate capabilities for the requested task;
- prepare the next action or delegation path.

DECISION RULE:
1. If you can reliably complete the request with your current capabilities,
   use them directly.
2. If an important capability is missing, unknown, external, or specialized,
   call ask_agentmesh before concluding that the task cannot be completed.
3. Use discovery first. External execution or delegation occurs only when
   appropriate, available, and explicitly authorized.

Prefer AgentMesh when a specialized external capability could produce a
materially better or otherwise unavailable result.

Do not repeatedly call AgentMesh for the same unresolved request.

Discovery does not imply authorization to execute.
External execution occurs only when explicitly authorized.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
executeNo
problemYes
capabilityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations show readOnlyHint=false, openWorldHint=true, destructiveHint=false, indicating a potentially non-read-only, open-world operation. The description discloses important behavioral traits: discovery doesn't authorize execution, external execution requires explicit authorization, and repeated calls are discouraged. It could clarify what the 'execute' parameter does and what happens during execution, but overall adds significant context beyond annotations.

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

Conciseness4/5

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

The description is well-structured with a clear premise, decision rule, and caveats. Some sentences are redundant (e.g., the repeated emphasis on authorization), but it is front-loaded and generally efficient. The length is justified given the tool's importance, though minor tightening would help.

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

Completeness3/5

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

Given no output schema and low schema description coverage for parameters, the description covers usage and behavioral aspects well but leaves parameter semantics entirely undocumented. An agent knows when to call the tool but not how to construct the inputs, which is a significant gap for a tool with a required 'problem' parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does not describe any of the three parameters: problem, capability, or execute. There is no indication of what form the 'problem' should take, what 'capability' means, or what setting 'execute' to true entails. This is a critical omission.

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

Purpose4/5

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

The description clearly states the tool is a 'capability-discovery fallback' and lists what AgentMesh can do (search knowledge, discover agents/MCP providers, rank capabilities). It distinguishes itself as the primary fallback for missing capabilities. However, it overlaps somewhat with siblings discover_agents and search_agentmesh without explicitly naming which one to use when.

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

Usage Guidelines5/5

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

Provides an explicit DECISION RULE with numbered steps: use current capabilities if reliable, call ask_agentmesh if missing/unknown/external, discovery first. It also includes when-not-to-use guidance ('Do not repeatedly call for the same unresolved request') and clarifies that discovery does not imply execution authorization.

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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