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Algenta MCP Server

by io.github.thyn-ai
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resume_agent_run

Resume a paused agent run by run_id. A run created with approval_mode=auto executes to completion synchronously and returns completed; a manual-mode run moves to requires_approval and still needs approve_agent_run. Resuming anything that is not paused fails with agent_run_invalid_state; an unknown run_id fails with agent_run_not_found. The transition is audit-logged and checkpointed. Returns the updated run resource.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "run_id": "<run_id>"
    },
    "name": "resume_agent_run"
  }
}

Input Schema

NameRequiredDescriptionDefault
run_idYesPaused run id from create_agent_run or list_agent_runs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / run_id / description
      Added value: +"Paused run id from create_agent_run or list_agent_runs."
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations are all false (readOnlyHint, idempotentHint, destructiveHint), so the description carries the full burden of disclosing behavior. It covers side effects ('audit-logged and checkpointed'), the state transition semantics (auto vs manual mode), error responses, and the return value ('updated run resource'). This is comprehensive for a state-changing operation.

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?

Four sentences, front-loaded with the core action, then progressively covering edge cases and side effects. Every sentence adds needed information without fluff; it is dense but not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description fully covers the return value, error conditions, and state-machine nuances. It even references where run_id originates, making it self-contained for correct invocation.

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?

The schema already documents run_id with 'Paused run id from create_agent_run or list_agent_runs.' (100% coverage). The description adds only the verb 'resume' without new parameter details, so it provides marginal value beyond the schema. Baseline 3 is appropriate.

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?

States the specific verb 'Resume' and resource 'paused agent run' by run_id, clearly distinguishing it from sibling operations like approve_agent_run and cancel_agent_run. The description explicitly references approval-mode behavior, making the tool's role in the lifecycle unambiguous.

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

Usage Guidelines5/5

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

Provides explicit guidance on when to use this tool versus approve_agent_run, stating that manual-mode runs 'still needs approve_agent_run' after resuming. It also lists failure conditions (invalid state, unknown run_id) that inform correct usage, effectively telling the agent when this tool is appropriate.

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

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