Skip to main content
Glama

tool_chain_orchestrator

Analyze user requests and generate structured tool execution plans by intelligently sequencing available MCP tools. Plan, execute, or validate multi-step workflows.

Instructions

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

Input Schema

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

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

No annotations provided. The description mentions 'AI-powered' but does not disclose behavioral traits, side effects, or auth requirements. The tool's impact on state (e.g., does it execute actions or just plan?) is ambiguous.

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?

Single sentence with clear, front-loaded purpose. No extraneous words; every word adds value.

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?

Given the high schema coverage and lack of output schema, the description provides adequate context. It could elaborate on the output format or execution behavior, but the schema handles parameters well.

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?

Input schema has 100% description coverage, so each parameter is already documented. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.

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?

Description clearly states the tool's function: 'AI-powered dynamic tool sequencing' that 'analyze user requests and generate structured tool execution plans'. This is a specific verb-resource combination, distinguishing it from sibling tools.

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?

No guidance on when to use this tool versus alternatives or when not to use it. The description lacks context for appropriate invocation contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tosin2013/mcp-adr-analysis-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server