ps_state_resume
Resume a halted AI agent with specified parameters to continue execution after governance checks.
Instructions
Resume a halted agent.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | ||
| reason | Yes | ||
| resetMetrics | No |
Resume a halted AI agent with specified parameters to continue execution after governance checks.
Resume a halted agent.
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | ||
| reason | Yes | ||
| resetMetrics | No |
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 tool resumes a halted agent, implying a state change operation, but doesn't describe what 'resume' entails (e.g., restarting execution, restoring state), potential side effects, permissions required, or error conditions. This is inadequate for a mutation 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 a single, efficient sentence with no wasted words. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
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 (state mutation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover parameter meanings, behavioral details, or return values, leaving the agent poorly equipped to use the tool correctly.
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 by explaining parameters. It mentions no parameters at all, leaving 'agentId', 'reason', and 'resetMetrics' undocumented. This fails to add meaning beyond the bare schema, creating significant gaps in understanding.
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 action ('Resume') and the target ('a halted agent'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'ps_state_halt' (which presumably halts agents) or other state management tools, missing explicit differentiation.
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 when an agent is halted, but provides no explicit guidance on when to use this tool versus alternatives like 'ps_state_reset' or 'ps_state_recalibrate', nor does it mention prerequisites or exclusions. This leaves the agent with minimal contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/chrbailey/promptspeak-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server