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analyze_paths

Trace user journey flows after a start event using a Sankey diagram. View nodes and links with user counts, including drop-offs and the long tail.

Instructions

Trace what users do AFTER a start event — the journey flow (Sankey) from the product's own events, so YOU can reason about real behaviour on your model. Returns nodes (the event at each depth, with distinct users + share of journeys) and links (source→target with how many users took that step), including where people drop off ('(exit)') and the collapsed long tail ('(other)'). Pass start to anchor on a specific event, or omit it to anchor on the most common journey start. Optional product_id (defaults to the primary product) and window_days (default 30).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startNoAnchor event name (optional; omit for the most common journey start).
product_idNoProduct id, from whoami (optional; primary by default).
window_daysNoWindow in days (default 30).
Behavior5/5

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

No annotations provided, so description carries full burden. Discloses output structure: nodes with distinct users and share, links with user counts, and special elements like '(exit)' and '(other)'. Fully describes what the tool returns and how it behaves.

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?

Description is informative but slightly long; front-loaded with purpose. Every sentence adds value, covering purpose, output, and parameters. Could be tightened slightly but remains efficient.

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

Completeness5/5

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

No output schema, so description compensates by detailing return values (nodes, links, drop-offs, long tail). All three optional parameters are explained with defaults. For a tool with no required parameters, this is comprehensive and leaves no ambiguity.

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 100% but adds minimal info (types and optionality). Description provides critical default behaviors for each parameter (start omitted = most common journey start, product_id defaults to primary, window_days defaults to 30). This significantly aids agent understanding beyond 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?

Clearly states the tool traces user journeys after a start event as a Sankey flow. Verb 'trace' and resource 'journey flow' are specific, and it distinguishes itself from the sibling 'analyze_funnel' by focusing on post-start event paths.

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?

Explains how to use optional parameters: start anchors to a specific event or defaults to the most common start, product_id and window_days have defaults. Does not explicitly contrast with alternatives like analyze_funnel, but provides enough context for correct invocation.

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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