Skip to main content
Glama

agent_stop

Stop a running agent by writing a stop record to the blackboard; the agent halts on its next poll. Requires agent ID.

Instructions

Signal a running agent to stop by writing a stop record to the blackboard and marking it stopped in the registry. Returns {ok:true, agentId, reason, stopped:true}. Returns {ok:false, error:"..."} if agent_id is missing. agent_id must match a value returned by agent_list; reason is optional but written to the audit log under eventType "agent_stop" and helps trace the cause of the stop. The agent observes the stop signal on its next poll — it does not terminate immediately. Call agent_list first to confirm the agent is currently active.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesID of the agent to stop
reasonNoReason for stopping (optional, for audit)
Behavior4/5

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

No annotations provided, but description discloses return values, error case, audit log writing, and the asynchronous nature of the stop. This gives a good understanding of tool behavior.

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?

Concise, front-loaded with main action, and every sentence provides necessary detail. No redundancy or unnecessary information.

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?

Despite no output schema, description explains the return format and covers async behavior. References agent_list appropriately. Adequately complete for a simple tool with good parameter documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and description adds value: agent_id must match agent_list, reason is optional but logged for auditing. This extra context aids correct invocation.

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?

Clearly states the tool signals a running agent to stop, with specific actions (writing blackboard record, marking registry). Distinguishes from siblings like agent_list and agent_spawn by mentioning that agent_id must match agent_list.

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

Usage Guidelines4/5

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

Explicitly advises to call agent_list first to confirm agent is active. Also explains the stop is asynchronous (next poll), setting proper expectations. Does not explicitly list when not to use, but context is clear.

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/Jovancoding/network-ai'

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