task-orchestrateTask Orchestrate — Break a multi-step task into an execution plan any agent can follow. Powered by api.meshtool.ai. Input: { task: string, tools: array }. (3 MESH/call, a tool · reasoning)
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Payload for task-orchestrate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only/destructive hints, and the description adds useful context: it is powered by an external API and costs 3 MESH per call. However, it does not disclose whether the tool executes the plan or only returns it, nor any side effects on state, memory, or external systems.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is quite short and front-loaded with the core purpose, but includes redundant 'Task Orchestrate —' and marketing-ish 'a tool · reasoning' text. The external API and pricing info are useful but could be more tightly integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain what the execution plan looks like or how the agent should use the result. It also lacks guidance on how this relates to sibling tools like task-analysis or agent-brain, leaving the agent to infer integration and output expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters. The description only restates 'Input: { task: string, tools: array }', adding no extra semantic detail about parameter usage, formatting, or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource: 'Break a multi-step task into an execution plan any agent can follow.' This clearly conveys the core function. However, it does not differentiate from the sibling tool 'task-analysis', which may serve a similar planning/analysis role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit statement about when to use this tool versus alternatives, nor any exclusion criteria. The phrase 'multi-step task' only implies usage context, but no clear when/when-not guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping purposes: search and mesh_discover both enumerate the catalog, while biz-analyze, task-analysis, and task-orchestrate all produce structured plans from a described situation. This will cause agents to misselect between them despite otherwise distinct tools.
Naming is inconsistent: mesh_* tools use snake_case, most capability tools use hyphenated lowercase names, and a few (fetch, search) are bare verbs. There is no single verb-object or noun-verb pattern that holds across the set.
28 tools is on the heavy side, but the marketplace concept justifies including many callable capabilities. However, the mix of platform tools and unrelated utilities makes the surface feel cluttered and hard to navigate.
The core marketplace lifecycle is well covered: signup, discover, fetch, publish, delegate, refer, follow, subscribe, and balance. Minor gaps exist (no unpublish or edit for listings), but most agent workflows can proceed without dead ends.