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Debug capture at

debug_capture_at

Stop a deployment at a specific source line to capture stack, scopes, and variables in one call. Use when logs and diagnostics aren't enough.

Instructions

Last-resort code debug for a deployment: stop at a source line and return stack/scopes/variables in one call. Use logs and diagnose tools first.

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": {
      "deployment_id": "<deployment_id>",
      "source": "<source>",
      "line": "<line>"
    },
    "name": "debug_capture_at"
  }
}

Input Schema

NameRequiredDescriptionDefault
lineYes
sourceYes
thread_idNo
timeout_msNo
deployment_idYesLocal managed language runtime deployment to debug. The agent resolves or creates the internal lease.
max_variablesNo
approval_tokenNo
variable_namesNo
approval_wait_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It explains the core action (stopping at a source line and returning data) and flags it as last resort, but it does not disclose side effects like pausing the deployment, approval requirements (despite approval_token in schema), or timeout behavior. The 'stop' implies a pause, but state-change implications are vague.

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?

Two concise sentences: the first packs purpose and behavior, the second gives usage guidance. No wasted words; every phrase contributes to understanding.

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

Completeness2/5

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

For a tool with 9 parameters, no output schema, and no annotations, this description is too sparse. It omits return format, approval workflow, side effects, and parameter rationale. The presence of many sibling debug tools further demands more contextual detail to guide selection and invocation.

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

Parameters2/5

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

Schema coverage is only 11%, and the description adds no parameter-specific meaning. It mentions stack/scopes/variables but does not connect them to parameters like variable_names, max_variables, or thread_id. The description fails to compensate for the under-documented schema.

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?

Description clearly states it is a 'last-resort code debug for a deployment' that stops at a source line and returns stack/scopes/variables in one call. This is a specific verb+resource combination and distinguishes it from siblings by emphasizing the combined one-call nature and last-resort positioning.

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 instructs to 'Use logs and diagnose tools first,' providing clear context for when not to use this tool. However, it does not name specific alternative tools among the extensive sibling list, so usage differentiation is not fully fleshed out.

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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