peon-orchestrator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ORCHAI_MODEL | Yes | Model to use, e.g., gpt-4o. | |
| ORCHAI_API_KEY | Yes | API key for OpenAI integration. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_agentsA | List all managed agents with status, busy flag, current task and task counts |
| spawn_agentC | Spawn a new agent with the given role and system prompt |
| stop_agentB | Stop a running agent |
| agent_statusC | Get the status of an agent |
| assign_taskA | Assign a task to an agent asynchronously. Returns task_id immediately. Use task_status and task_result to track progress. |
| task_statusB | Get detailed status of a specific task including missing_tools, partial flag, and timestamps. |
| task_resultB | Get the result of a task enriched with task_id and status. If task_id is omitted, returns the last result. |
| aggregate_resultsC | Aggregate results for multiple tasks including missing_tools, status and output. |
| broadcastA | Send a message to all running agents in parallel. Returns list of {agent_id, task_id}. |
| read_storageC | Read data from shared storage |
| write_storageB | Write data to shared storage. Handles JSON strings automatically. Protected keys are restricted. |
| list_storageA | List all keys in shared storage |
| storage_cleanupA | Remove keys from storage matching a glob pattern with optional exclusion. |
| cleanup_task_historyC | Remove old tasks from history. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 14 tools
Most tools are clearly distinct: agent lifecycle tools (list, spawn, stop, status) and task tools (assign, status, result, aggregate) separate cleanly. Minor overlap exists between list_agents and agent_status since list_agents already includes status fields, but descriptions clarify the singular focus of agent_status. Storage tools are unambiguous.
Naming mixes conventions: verb_noun (list_agents, spawn_agent, assign_task, read_storage, write_storage, aggregate_results), noun_noun (task_status, task_result, agent_status), and single verb (broadcast). While readable, the pattern is not uniform and violates expectations (e.g., agent_status vs status_agent, storage_cleanup vs cleanup_storage).
14 tools is within a reasonable range for an orchestrator covering agent lifecycle, task management, and shared storage. Each tool serves a distinct purpose and the count reflects the breadth of functionality without being excessive.
The tool surface covers core workflows well: agent creation/listing/removal/status, task assignment/tracking/results/aggregation, and storage read/write/cleanup. Minor gaps like a direct task cancellation or agent update are missing, but these are edge cases not fundamental to the domain.