Claude Code MCP - Agent Orchestration Platform
Orchestrates multiple Claude Code agents across iTerm2 terminal sessions using tab-based management, enabling creation and deletion of sessions, agent management, and inter-agent communication through task-based workflows.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Claude Code MCP - Agent Orchestration Platformcreate a new agent for my React project at /Users/alice/projects/ecommerce"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Claude Code MCP - Agent Orchestration Platform
Overview
A sophisticated FastMCP Python server that orchestrates multiple Claude Code agents across iTerm2 sessions, providing centralized management and inter-agent communication through task-based workflows.
Related MCP server: claude-swarm
Architecture
Agent Orchestration Platform with:
iTerm2 Tab-Based Sessions: No window complexity, pure tab management
Persistent Agent State: Survives iTerm restarts with state recovery
Codebase-Linked Sessions: Sessions tied to specific root filepaths
Maximum Security Isolation: Process-level separation between agents
Task-Based Inter-Agent Communication: ADDER+ workflow coordination
System Prompt Injection: Automatic Agent_# naming and prompt prepending
Core MCP Tools
Tool | Purpose | Security Level |
| Creates new Claude Code agent instance | HIGH |
| Removes agent from system | HIGH |
| Creates session tied to root filepath | MEDIUM |
| Returns status of all agents in session | LOW |
| Removes entire session and all agents | HIGH |
| Sends message with ADDER+ prepending | MEDIUM |
| Closes current iTerm tab for agent | MEDIUM |
| Opens new iTerm tab for agent | MEDIUM |
ADDER+ Workflow Integration
Each agent operates with the comprehensive ADDER+ (Advanced Development, Documentation & Error Resolution) protocol, enabling:
Autonomous Task Management: TODO.md-driven execution with real-time progress tracking
Advanced Programming Synthesis: Design by Contract + defensive programming + type-driven development + property-based testing + functional programming patterns
Systematic Error Resolution: Root Cause Analysis with automatic task generation
Inter-Agent Coordination: Task-based communication through documentation files
Security Model
Process Isolation: Each Claude Code agent runs in separate process
Session Boundaries: Agents cannot access other session codebases
State Encryption: Persistent agent state encrypted at rest
Audit Logging: All agent interactions logged for security analysis
Permission Model: Role-based access control for agent operations
Quick Start
# Install dependencies
uv sync
# Start the MCP server
python src/main.pyClaude Desktop Configuration
To use this Agent Orchestration Platform with Claude Desktop, you need to configure it as an MCP server in Claude's configuration file.
Configuration File Location
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%/Claude/claude_desktop_config.jsonConfiguration Steps
Open Configuration File: Navigate to the configuration file location above. Create the file if it doesn't exist.
Add Server Configuration: Add the following configuration to your
claude_desktop_config.json:
Option 1: Using UV (Recommended)
{
"mcpServers": {
"claude-code-mcp": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/Claude_Code_MCP",
"run",
"python",
"src/main.py"
],
"env": {
"PYTHONPATH": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/src"
}
}
}
}Option 2: Using Python Directly
{
"mcpServers": {
"claude-code-mcp": {
"command": "python",
"args": [
"/ABSOLUTE/PATH/TO/Claude_Code_MCP/src/main.py"
],
"env": {
"PYTHONPATH": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/src"
}
}
}
}Option 3: Using Virtual Environment
{
"mcpServers": {
"claude-code-mcp": {
"command": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/.venv/bin/python",
"args": [
"/ABSOLUTE/PATH/TO/Claude_Code_MCP/src/main.py"
],
"env": {
"PYTHONPATH": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/src"
}
}
}
}Configuration Notes
Replace
/ABSOLUTE/PATH/TO/Claude_Code_MCPwith the actual absolute path to your project directoryOn Windows, use backslashes in paths:
C:\\path\ o\\Claude_Code_MCPServer Name: You can change
"claude-code-mcp"to any name you preferVirtual Environment: If using a virtual environment, adjust the Python path accordingly
Advanced Configuration Options
With Custom Security Level
{
"mcpServers": {
"claude-code-mcp": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/Claude_Code_MCP",
"run",
"python",
"src/main.py",
"--security-level",
"HIGH",
"--max-agents",
"16",
"--max-sessions",
"8"
],
"env": {
"PYTHONPATH": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/src"
}
}
}
}With Custom Log Directory
{
"mcpServers": {
"claude-code-mcp": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/Claude_Code_MCP",
"run",
"python",
"src/main.py",
"--log-dir",
"/ABSOLUTE/PATH/TO/Claude_Code_MCP/logs"
],
"env": {
"PYTHONPATH": "/ABSOLUTE/PATH/TO/Claude_Code_MCP/src"
}
}
}
}Verification Steps
Save Configuration: Save the
claude_desktop_config.jsonfileRestart Claude Desktop: Completely quit and restart Claude Desktop
Check MCP Status: Look for MCP server indicators in the Claude Desktop interface:
Hammer icon (🔨) indicating available tools
Connector icon indicating MCP server connection
Test Functionality: Try using one of the agent orchestration tools
Troubleshooting
Server Not Loading
Verify all paths are absolute (not relative)
Check that
uvorpythonis in your system PATHEnsure the project directory exists and has correct permissions
Review Claude Desktop logs at:
macOS:
~/Library/Logs/Claude/mcp*.logWindows:
%APPDATA%\Claude\logs\mcp*.log
Manual Testing
Test the server manually before configuring Claude Desktop:
# Navigate to project directory
cd /path/to/Claude_Code_MCP
# Test with UV
uv run python src/main.py --help
# Test with Python directly
python src/main.py --helpCommon Issues
Permission Errors: Ensure Claude Desktop has permission to execute the Python interpreter
Import Errors: Verify
PYTHONPATHis correctly set in the configurationPort Conflicts: If using HTTP transport, ensure the port (default 8000) is available
Available MCP Tools
Once configured, Claude Desktop will have access to these agent orchestration tools:
create_agent- Create new Claude Code agent instancesdelete_agent- Remove agents from the systemcreate_session- Create sessions tied to specific codebasesget_session_status- Get status of all agents in a sessiondelete_session- Remove entire sessions and all agentssend_message_to_agent- Send messages with ADDER+ protocol integrationclear_agent_conversation- Close current iTerm tab for agentstart_new_agent_conversation- Open new iTerm tab for agent
Development Workflow
Session Creation: Link sessions to specific codebases
Agent Spawning: Create specialized agents with custom system prompts
Task Coordination: Agents communicate through TODO.md and task files
Status Monitoring: Real-time visibility into agent progress and health
Session Management: Persistent state with recovery capabilities
Integration Points
FastMCP Framework: High-performance MCP server implementation
iTerm2 Python API: Advanced terminal session management
Claude Code: AI agent process orchestration
Asyncio Architecture: Event-driven concurrent agent management
This platform enables sophisticated AI development workflows with multiple specialized agents working collaboratively on complex codebases while maintaining strict security isolation and comprehensive audit trails.
Available Tools
7 toolscreate_agentB
Create a new Claude Code agent within a managed session.
Creates a new agent instance with the specified configuration and assigns it to the given session for collaborative development work.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | ||
| agent_name | Yes | ||
| specialization | No | ||
| system_prompt_suffix | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states this is a creation operation but doesn't disclose behavioral traits like required permissions, whether this is idempotent, what happens on duplicate agent names, rate limits, or what the response contains. For a mutation tool with zero annotation coverage, this is a significant gap.
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?
Two sentences, front-loaded with the core purpose. The second sentence adds useful context about configuration and assignment. No wasted words, though it could be slightly more structured with bullet points for parameters given the low schema coverage.
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?
For a mutation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or detailed parameter meanings. Given the complexity and lack of structured data, the description should provide more comprehensive guidance.
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 0%, so the description must compensate but adds minimal parameter semantics. It mentions 'specified configuration' vaguely but doesn't explain what the 4 parameters mean, their relationships, or constraints. The description doesn't clarify what 'specialization' or 'system_prompt_suffix' do, leaving parameters largely undocumented.
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 clearly states the verb ('Create') and resource ('new Claude Code agent') with specific context ('within a managed session'). It distinguishes from siblings like 'create_session' (creates session vs agent) and 'delete_agent' (destructive vs constructive). The purpose is specific and unambiguous.
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?
The description implies usage context ('within a managed session', 'for collaborative development work') but doesn't explicitly state when to use this vs alternatives like 'create_session' or prerequisites. It mentions assignment to a session but lacks explicit guidance on when-not-to-use or comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_sessionC
Create a new development session for a project.
Initializes a new session with the specified root path and prepares the environment for agent collaboration.
| Name | Required | Description | Default |
|---|---|---|---|
| root_path | Yes | ||
| session_name | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions initializing a session and preparing the environment for agent collaboration, which implies setup actions, but lacks details on permissions required, whether this is idempotent, what happens on failure, or any rate limits. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 appropriately sized with two sentences that are front-loaded: the first states the purpose, and the second adds context about initialization and environment preparation. There's no wasted text, making it efficient, though it could be slightly more structured for clarity.
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 the tool's complexity (creation operation with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover what the tool returns (e.g., session ID, status), error conditions, or detailed behavioral aspects. For a tool that likely has side effects, this leaves the agent with insufficient information to use it effectively.
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 0%, so the schema provides no parameter details. The description adds minimal semantics by mentioning 'specified root path' and implying session initialization, but it doesn't explain what root_path or session_name represent (e.g., file paths, identifiers), their formats, or constraints. This partially compensates for the lack of schema descriptions but falls short of fully clarifying parameter meanings.
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 clearly states the tool creates a new development session for a project, specifying the action (create/initialize) and resource (session). It distinguishes from siblings like delete_session or get_session_status by focusing on creation rather than deletion or querying. However, it doesn't explicitly differentiate from create_agent, which might be a related but distinct operation.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether a project must exist), when not to use it (e.g., if a session already exists), or direct alternatives among siblings like list_sessions for checking existing sessions. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_agentA
Delete an agent from the system.
Safely terminates and removes an agent from its session. Use force=True to forcefully terminate unresponsive agents.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_name | Yes | ||
| force | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Safely terminates and removes an agent from its session,' which implies a destructive operation with some safety measures, but it does not detail permissions required, irreversible consequences, error conditions, or what happens to associated resources. The force parameter behavior is noted, but overall behavioral context is incomplete.
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 front-loaded with the core purpose, followed by behavioral and parameter details in two concise sentences. Every sentence adds value: the first states the action, the second describes safety and the force parameter. There is no wasted text, and the structure is efficient.
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 the tool's complexity (destructive operation with 2 parameters), no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and force parameter usage but lacks details on permissions, error handling, return values, and full parameter semantics. It meets minimum viability but has clear gaps for a deletion tool.
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 0%, so the description must compensate. It explains the purpose of the force parameter ('to forcefully terminate unresponsive agents'), adding meaningful context beyond the schema's boolean type. However, it does not clarify the agent_name parameter's format or constraints. The description partially compensates but leaves one parameter undocumented.
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 clearly states the specific action ('Delete') and target resource ('an agent from the system'), distinguishing it from sibling tools like delete_session (which targets sessions) and create_agent (which creates rather than deletes). The verb+resource combination is precise and unambiguous.
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?
The description provides clear context for when to use the force parameter ('to forcefully terminate unresponsive agents'), but it does not explicitly state when to use this tool versus alternatives like delete_session or when deletion is appropriate versus other operations. The guidance is helpful but lacks sibling differentiation and exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_sessionA
Delete a session and all its agents.
Safely terminates all agents in the session and cleans up resources. Use force=True to forcefully terminate unresponsive sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | ||
| force | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: 'Safely terminates all agents in the session and cleans up resources' explains the destructive nature and cleanup process, while the force parameter guidance addresses handling of unresponsive sessions. It doesn't mention error conditions, permissions, or rate limits, but provides solid core behavioral context.
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?
Three sentences with zero waste: the first states the purpose, the second explains the safe behavior, the third provides parameter guidance. Each sentence earns its place, and the structure is front-loaded with the core action followed by important details.
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?
For a destructive tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the main behavior and parameter usage but lacks information about return values, error conditions, permissions required, or what happens if the session doesn't exist. Given the complexity of session/agent management, more completeness would be helpful.
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?
With 0% schema description coverage, the description must compensate for the lack of parameter documentation. It does this well by explaining the purpose of the force parameter ('to forcefully terminate unresponsive sessions') and implying session_id identifies the target session. While it doesn't detail session_id format or constraints, it provides meaningful semantic context beyond the bare schema.
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 clearly states the specific action ('Delete a session and all its agents') and distinguishes it from sibling tools like delete_agent (which deletes individual agents) and list_sessions/get_session_status (which are read-only). The verb+resource combination is precise and unambiguous.
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?
The description provides clear context for when to use the force parameter ('to forcefully terminate unresponsive sessions'), which implicitly suggests when to use the default (force=False) for normal termination. However, it doesn't explicitly state when to choose this tool over alternatives like delete_agent or provide prerequisites for session deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_session_statusC
Get the current status of a session and its agents.
Returns comprehensive status information about the session including all active agents and their current state.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns 'comprehensive status information' but doesn't specify what that includes (e.g., agent states, session metadata, timestamps) or behavioral traits like error handling, performance characteristics, or authentication requirements. The description is too vague for a mutation-free tool with zero annotation coverage.
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 appropriately sized with two sentences that are front-loaded: the first states the core purpose, and the second elaborates on the return value. There's minimal redundancy, though it could be slightly more efficient by combining ideas.
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 the tool's moderate complexity (status retrieval with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return structure, error conditions, or parameter details, leaving significant gaps for an AI agent to use the tool effectively.
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 0%, so the description must compensate for undocumented parameters. It doesn't mention the session_id parameter at all, leaving its purpose, format, or sourcing unclear. The description adds no semantic value beyond what the bare schema provides, failing to address the coverage gap.
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 clearly states the tool's purpose with specific verbs ('Get', 'Returns') and resources ('status of a session and its agents', 'comprehensive status information'). It distinguishes from siblings by focusing on status retrieval rather than creation, deletion, listing, or messaging. However, it doesn't explicitly differentiate from similar status-checking tools that might exist.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid session_id), compare to sibling tools like list_sessions for broader overviews, or specify use cases (e.g., monitoring agent activity). Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sessionsB
List all active sessions and their basic information.
Returns a summary of all currently active sessions in the system.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns 'a summary of all currently active sessions' but doesn't specify what 'basic information' or 'summary' includes, whether there are pagination limits, rate limits, authentication requirements, or what 'active' means in this context. The description provides minimal behavioral context beyond the basic operation.
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 appropriately concise with two clear sentences that directly state the tool's function. The first sentence establishes the core purpose, and the second reinforces it without redundancy. There's no wasted language, though it could be slightly more front-loaded by combining the two sentences.
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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does at a high level but lacks details about the return format, what constitutes 'active' sessions, or how this differs from related session management tools. For a read-only listing operation, more context about the output would be helpful since there's no output schema.
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?
The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it correctly focuses on what the tool does rather than trying to explain non-existent inputs.
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 clearly states the verb ('List') and resource ('all active sessions and their basic information'), making the tool's purpose explicit. It distinguishes from siblings like 'get_session_status' by focusing on listing all active sessions rather than checking a specific session. However, it doesn't explicitly differentiate from other list-like operations that might exist in the broader context.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'list_sessions' over 'get_session_status' for checking individual sessions, or how it relates to session creation/deletion tools. There's no context about prerequisites, timing, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_message_to_agentC
Send a message to a specific agent.
Delivers a message to the specified agent for processing. The agent will receive the message and can respond accordingly.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_name | Yes | ||
| message | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the agent 'will receive the message and can respond accordingly,' which implies a communication flow but lacks details on permissions, rate limits, error handling, or whether this is a synchronous or asynchronous operation. This leaves significant gaps in understanding the tool's behavior.
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 appropriately sized with two sentences that are front-loaded and avoid redundancy. The first sentence states the purpose clearly, and the second adds context without unnecessary elaboration. It could be slightly more structured but earns its place efficiently.
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 the complexity of messaging between agents, no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover response formats, error cases, or integration with sibling tools like sessions, leaving the agent with insufficient context for reliable use.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it implies 'agent_name' identifies the recipient and 'message' is the content sent. However, it doesn't explain format constraints, valid agent names, or message handling, failing to compensate for the low coverage.
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 clearly states the tool's purpose: 'Send a message to a specific agent' and 'Delivers a message to the specified agent for processing.' It uses specific verbs ('send,' 'delivers') and identifies the resource ('agent'), but it doesn't differentiate from sibling tools like 'create_agent' or 'get_session_status,' which involve different operations on agents or sessions.
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?
The description provides no guidance on when to use this tool versus alternatives. It mentions that the agent 'can respond accordingly,' but this is vague and doesn't specify context, prerequisites, or exclusions. For example, it doesn't clarify if this is for real-time communication, asynchronous messaging, or how it relates to sessions or other agent interactions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a clearly distinct purpose with no overlap: create/delete for agents and sessions, status retrieval, listing, and message sending. The descriptions reinforce these boundaries, making it easy for an agent to select the right tool without confusion.
All tools follow a consistent verb_noun pattern (e.g., create_agent, delete_session, get_session_status). The naming is uniform across all 7 tools, with no deviations in style or convention, ensuring predictability and readability.
With 7 tools, the set is well-scoped for an agent orchestration platform. It covers core operations like session/agent lifecycle management, status monitoring, and communication, with each tool earning its place without being excessive or insufficient.
The toolset provides strong coverage for session and agent management, including CRUD operations and messaging. A minor gap exists in lacking tools for updating agent configurations or session properties, but agents can work around this by recreating resources as needed.
Maintenance
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