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Debug Trace

synapse_debug_trace

Trace execution flow or resolve runtime crash stack traces to pinpoint root causes and debug issues in indexed code.

Instructions

Traces code paths or resolves error stack traces to understand execution flow and debug issues. High-level actions include:

  • 'trace_behaviour': maps the execution flow of a function (branching, state access, side effects, tests).

  • 'resolve_stack': parses a runtime crash stack trace and matches frames to repository chunks, root cause, and tests.

REPLACES: manual stack trace reading, grep_search for error origins, sequential file reads to trace execution. Use this tool instead of these alternatives for better results with 30-60% fewer tokens via automatic compression.

Usage (short): Trace ranked execution paths and map crash stack traces to code chunks. Maps stack traces to chunks.

Usage (long): Trace execution flow (branching, state access, side effects) or resolve runtime stack traces to locate crash-site causes and tests. Use 'trace_behaviour' to understand how a function works without running it. Use 'resolve_stack' to map crash stack traces to indexed code chunks with root cause analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesThe action to perform.
max_tokensNoApproximate final response budget in tokens (500-32000, default 4000).
compress_payloadNoSet false to disable lossless response-key compression.
Behavior3/5

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

With no annotations, the description carries the full behavior burden. It does disclose that the tool does not run code and that it reduces token usage via automatic compression. However, it does not mention potential side effects of the save_to_file parameter, any indexing/prerequisite requirements, or whether resolution can fail for unknown stacks, so the transparency is incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and organized into scannable sections: actions, REPLACES, short usage, and long usage. There is some redundancy between the short and long usage sections, but each section generally earns its place.

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?

For a 3-parameter tool with no output schema and no annotations, the description provides enough context to understand what the tool does, when to choose each action, and what results conceptually look like. It does not fully describe output structure or prerequisite conditions, but the prose covers most of what an agent needs.

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

Parameters4/5

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

The input schema already covers all three parameters with high description coverage, giving a baseline of 3. The tool description adds meaningful semantics to the action enum by explaining exactly what 'trace_behaviour' and 'resolve_stack' do, while the schema still handles the function signature and save_to_file details.

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 specific verb and resource ('Traces code paths or resolves error stack traces...') and names two concrete high-level actions, each with clear inputs and outcomes. It clearly distinguishes this tool from the sibling tools like synapse_search_codebase or synapse_inspect_files.

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?

It explicitly states what this tool replaces: manual stack trace reading, grep_search for error origins, and sequential file reads, and tells the agent to use this instead. It also gives action-specific guidance: use trace_behaviour to understand function flow without running it, and use resolve_stack to map crash frames to chunks and root cause.

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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