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trace-mcp

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get_task_context

Read-onlyIdempotent

Get all-in-one task context: execution paths, tests, and entry points adapted to your task type. Use as the first call when starting any dev task to replace manual searches.

Instructions

All-in-one context for starting a dev task: execution paths, tests, entry points, adapted by task type. Use as your FIRST call when beginning any new task — replaces manual chaining of search → get_symbol → Read. For narrower feature-code lookup use get_feature_context instead. Read-only. Returns JSON (default) or Markdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesNatural language description of the task
focusNoContext strategy: minimal (fast, essential only), broad (default, wide net), deep (follow full execution chains)
detail_levelNoOutput verbosity. "minimal" saves ~40-60% tokens (drops scores, fqn, signatures, summaries). Use to pick a candidate before get_symbol. Default: "default".
token_budgetNoMax tokens (default 8000)
include_testsNoInclude relevant test files (default true)
output_formatNo"json" (default, structured fields) or "markdown" (single LLM-optimized document with code fences, ~15-20% cheaper).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.31.0
    • changedInput schema / properties / detail_level / description
      Previous value: -"Output verbosity. \"minimal\" returns ~40-60% fewer tokens (drops scores, fqn, signatures, summaries — keeps name/file/line). Use when you only need to pick a candidate before drilling in with get_symbol. Default: \"default\"."New value: +"Output verbosity. \"minimal\" saves ~40-60% tokens (drops scores, fqn, signatures, summaries). Use to pick a candidate before get_symbol. Default: \"default\"."
  2. Changed3 schema fields changedv3.3.0
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • addedInput schema / properties / detail_level
      Added value: +{
+  "description": "Output verbosity. \"minimal\" returns ~40-60% fewer tokens (drops scores, fqn, signatures, summaries — keeps name/file/line). Use when you only need to pick a candidate before drilling in with get_symbol. Default: \"default\".",
+  "enum": [
+    "minimal",
+    "default",
+    "full"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / output_format / description
      Previous value: -"Output format. \"json\" (default) returns structured fields; \"markdown\" returns a single LLM-optimized document with code fences (~15-20% token savings)."New value: +"\"json\" (default, structured fields) or \"markdown\" (single LLM-optimized document with code fences, ~15-20% cheaper)."
  3. Added
  4. Removedv1.38.0
  5. Changed2 schema fields changedv1.35.1
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / output_format
      Added value: +{
+  "description": "Output format. \"json\" (default) returns structured fields; \"markdown\" returns a single LLM-optimized document with code fences (~15-20% token savings).",
+  "enum": [
+    "json",
+    "markdown"
+  ],
+  "type": "string"
+}
  6. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful behavioral context beyond annotations: outputs are adapted by task type, it returns JSON or Markdown, and it consolidates what would otherwise require multiple tools. It doesn't go into response structure or cost details, but it meaningfully exceeds what annotations alone provide.

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 tightly packed sentences with zero filler. The most actionable instruction ('Use as your FIRST call') is front-loaded, and both the sibling differentiation and return format are stated in a single breath.

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 six parameters, a rich annotation set, and no output schema, the description covers nearly everything an agent needs: purpose, timing, alternatives, content delivered, and output format. It would be complete with a hint about response fields beyond 'execution paths, tests, entry points', but the schema covers the parameters and the description covers usage context.

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?

Schema description coverage is 100%, so the schema already documents all six parameters thoroughly in terms of enums, defaults, and token impact. The description only lightly references output_format ('Returns JSON (default) or Markdown') and the task type adaptation, adding marginal value beyond the schema's own param descriptions.

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 opens with a concrete, specific purpose: 'All-in-one context for starting a dev task' and enumerates the included content (execution paths, tests, entry points). It explicitly differentiates from the sibling tool get_feature_context, making the intent unmistakable against the surrounding toolset.

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 when-to-use guidance: 'Use as your FIRST call when beginning any new task.' It even names the workflow it replaces ('search → get_symbol → Read') and points to the correct alternative for narrower lookups (get_feature_context). This is model behavior for routing an agent.

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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