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trace

Read-only

Follow code across service boundaries by tracing a feature end-to-end or finding the shortest path between nodes, each hop labeled with its mechanism.

Instructions

Follow the code across boundaries. One argument: trace a feature end-to-end — the ordered path from entry through the stack, each hop labelled with its mechanism (call / HTTP / queue / event / data), crossing service boundaries (frontend→backend). Two arguments: the shortest path between two specific nodes, hop by hop. This is where the graph beats reading many files — it knows the cross-stack links grep can't see.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoMax hops for the cross-stack feature trace. Default 6.
budgetNoMax chars in the result. 0 = no cap.
to_nodeNoOptional target node. Given → shortest path from_node→to_node. Blank → trace `from_node` as a feature across the stack.
from_nodeYesA feature/keyword to trace end-to-end (one arg), OR the start node when tracing a path to `to_node`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations declare readOnlyHint=true, so the agent knows it's a read operation. The description adds behavioral detail: the tool traverses service boundaries, labels mechanisms (call/HTTP/queue/event/data), and behaves differently with one vs two arguments. No contradictions.

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 concise: four sentences, front-loaded with the purpose, each sentence adding value (action, mode distinction, justification). No wasted words.

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 4 parameters, an output schema, and moderate complexity, the description covers the core behavior and use cases. It does not detail node types or mechanism labels, but provides enough for an agent to select the tool appropriately.

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?

Schema description coverage is 100%, baseline 3. The description adds meaning by explaining the dual behavior of from_node (feature or start node) and to_node (target node for shortest path), which complements the schema 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 clearly states the tool traces code across boundaries, explains one-argument (feature end-to-end) and two-argument (shortest path) modes, and distinguishes from siblings like find and impact by emphasizing cross-stack links that grep cannot see.

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?

The description explains that the tool is used for tracing features end-to-end or finding paths between nodes, and contrasts with reading files/grep. It does not explicitly state when not to use it versus specific siblings, but the context is clear enough.

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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