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Get a whole journey

get_journey
Read-onlyIdempotent

Get every screen of one user journey from UXKIN, in order, with the screenshots attached as images (up to 10): for example all 8 screens of "Deleting account" in one app. Use it after find_ui_references returns a result of type journey, passing that result's id (and its appId when there is one), to study the whole flow (each step, confirmations, the end state) instead of only its first screen.

Input Schema

NameRequiredDescriptionDefault
app_idNoOptional: the result's appId, e.g. "a_lbNUWzdsYls3".
journey_idYesThe journey's id from a find_ui_references result, e.g. "j_kFcZd3I-jm6c".

Output Schema

NameRequiredDescriptionDefault
idYes
appYes
hrefYesThe journey on uxkin.com.
nameYesWhat the journey does, e.g. "Deleting account".
screensYesThe journey's screens, in order.
screenCountYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-obvious behavior: results are ordered and include screenshots as images with a cap of 10. It does not mention pagination or what happens when a journey exceeds 10 screens, which is the only real gap.

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?

It is a single, front-loaded sentence that opens with the concrete outcome (every screen, in order, with images) before the usage instructions. It is dense but every clause carries information; only the nested example adds mild verbosity.

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?

An output schema exists, so return-value documentation is unnecessary, yet the description still conveys the salient return traits (ordered screens, attached screenshots, 10-item cap). Combined with the full schema coverage and annotations, an agent has everything needed to select and call this correctly.

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 both parameters are already documented with examples in the schema itself. The description reinforces the provenance of journey_id (from a find_ui_references result) and the optional appId, but adds little syntax or meaning beyond what the schema states, so this lands at the baseline.

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 names a specific verb and resource ('Get every screen of one user journey from UXKIN, in order') and adds concrete scope detail (screenshots attached, up to 10 screens, ordered). It is clearly distinguishable from siblings like find_ui_references and get_collection, which deal with references and collections rather than a full journey.

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 states the exact trigger ('after find_ui_references returns a result of type journey'), the inputs to pass ('that result's id (and its appId when there is one)'), and the intent ('to study the whole flow ... instead of only its first screen'). That is explicit when-to-use plus an implicit alternative, leaving little to inference.

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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