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tool_chain_orchestrator

Analyze user requests to generate structured, dynamic tool execution plans for efficient AI-powered sequencing.

Instructions

AI-powered dynamic tool sequencing - intelligently analyze user requests and generate structured tool execution plans

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxStepsNoMaximum number of steps in the execution plan
userRequestYesUser request to analyze and create tool execution plan for
contextHintsNoAdditional context hints for better plan generation
allowParallelNoAllow parallel execution of independent steps
executionModeNoOrchestration modeplan_only
availableToolsNoList of available MCP tools to orchestrate
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only says 'generate structured tool execution plans', omitting that the tool can also execute plans (executionMode), requires a list of available tools, or returns a plan. It does not mention side effects, rate limits, or dependencies.

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 a single sentence that conveys the main purpose. It is front-loaded with the key phrase 'AI-powered dynamic tool sequencing'. However, it could be improved by adding a second sentence summarizing usage.

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

Completeness2/5

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

The tool is a complex orchestrator with 6 parameters and no output schema. The description fails to explain what the tool returns (execution plan), the meaning of modes (plan_only vs plan_and_execute), or the role of availableTools. It is insufficient for an agent to use correctly without further context.

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% (all 6 parameters have descriptions). The tool description adds no additional meaning beyond the schema, so the baseline of 3 is appropriate. It does not explain parameter interplay or provide examples.

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 states the tool's core function: analyzing user requests and generating tool execution plans. It distinguishes itself from sibling tools (specific analyzers and utilities) by being an orchestrator, though the term 'AI-powered dynamic tool sequencing' is somewhat buzzwordy.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention that it is intended for multi-step workflows, nor does it contrast with sibling tools like 'mcp_planning' or 'analyze_*' tools. The agent receives no context to decide when to invoke it.

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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