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netcoredbg-mcp

netcoredbg-mcp

by thebtf
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_trace_log

Read-onlyIdempotent

Retrieve tracepoint evaluation logs to debug .NET applications. Filter entries by timestamp or specific tracepoint ID for targeted analysis.

Instructions

Get tracepoint evaluation log.

State: Works in any state.

Args: since: Only return entries after this timestamp (monotonic) tracepoint_id: Filter to specific tracepoint

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_trace_log"
  }
}

Input Schema

NameRequiredDescriptionDefault
sinceNo
tracepoint_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.17.2

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds the state constraint ('Works in any state'), which is useful context beyond annotations. No contradictions or omissions.

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?

The description is extremely concise with two sentences for purpose and two lines for parameters, no wasted words. Information is front-loaded and efficiently structured.

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?

Given the tool's simplicity and annotations, the description covers purpose, state, and parameter meanings. However, it lacks details about return format or pagination, which could aid completeness.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully compensates by explaining both parameters: 'since' for timestamp filtering and 'tracepoint_id' for specific tracepoint filtering. This adds meaning beyond the schema's type and default.

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?

The description clearly states the action 'Get tracepoint evaluation log,' which is a specific verb and resource. It is distinct from sibling tools like 'add_tracepoint' or 'clear_trace_log'.

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

Usage Guidelines3/5

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

The description mentions 'Works in any state,' providing minimal usage context. However, it lacks when-to-use or alternatives, and does not differentiate from similar tools like 'clear_trace_log' or 'list_breakpoints'.

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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