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UI Verify

by io.github.igrlk

Get per-story diff detail with image URLs

get_diff
Read-only

Per-story diff detail for a build (resolved by commitSha/prNumber/buildId). Returns diff metrics and presigned, time-limited URLs (download them to a file, or link them in a PR comment) for the baseline, candidate, and diff PNGs. Defaults to the changed stories; pass storyId for one specific story. When that storyId is an UNCHANGED story it returns its baseline (diffResultId null, changed false, the baseline URL as both baselineUrl and candidateUrl) - the story rendered identical to baseline. Use render_diff_image instead when you want the actual pixels inline for a vision model, not a URL. When AI review is on, each diff carries the judge's call: aiVerdict (intended|regression), aiConfidence, aiSummary (what changed), aiReasoning, and aiFlagReason; all null when AI review didn't run for it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
buildIdNoResolve this exact build id.
storyIdNoLimit to one story id.
prNumberNoResolve the latest build for this PR number.
commitShaNoResolve the build for this git commit SHA.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
diffsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, and the description matches that by describing a read-only detail query. It adds valuable behavioral context beyond annotations: URLs are presigned and time-limited, unchanged stories return a special shape with diffResultId null and changed false, and AI review fields are null when review did not run. No contradiction with annotations exists.

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 dense and front-loaded, starting with the core purpose and resolution paths. It packs necessary usage, edge-case, alternative-tool, and AI-field behavior into a few sentences. The AI field enumeration is slightly long, though useful, which keeps it from a perfect score.

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 read-only tool with an output schema and four optional-looking parameters, the description is largely complete: it covers resolution paths, defaults, the main edge case, URL behavior, and the close sibling alternative. A minor gap is that it does not state what happens if no build identifier is supplied, even though the schema lists all parameters as optional.

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 schema already covers 100% of parameters with brief descriptions, so the baseline is 3. The description adds meaning beyond that by explaining the default behavior of storyId (default to changed stories) and the unusual unchanged-story result semantics. It does not add much per-parameter syntax, but the added scope and edge-case semantics justify one point above 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 states a specific verb and resource ('Per-story diff detail for a build') and immediately clarifies the resolution paths (commitSha/prNumber/buildId). It also distinguishes itself from a close sibling by saying 'Use render_diff_image instead when you want the actual pixels inline for a vision model, not a URL.' This lets an agent separate get_diff from render_diff_image without opening schemas.

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?

The description gives explicit when-to-use guidance: get_diff is for diff metrics and URLs, and render_diff_image is the alternative when inline pixel data is needed. It also explains the default story scope, the optional storyId override, and the unchanged-story edge case, which is exactly the kind of usage context an agent needs.

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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TDQS

A4.7/5.0
Disambiguation4/5

Most tools target distinct resources and actions, and the descriptions carefully separate build triage from PR changesets. However, get_diff and render_diff_image both provide diff imagery (URLs vs inline), and accept_build overlaps with review_diff's accept mode, so one or two selections could be mis-picked without reading closely.

Naming Consistency5/5

All nine tools use a consistent snake_case verb_noun pattern: list_* for paginated listings, get_* for detail/triage, render_* for image output, and review_diff/accept_build for review actions. The naming convention is predictable and easy to reason about.

Tool Count5/5

Nine tools is well within the ideal scope for a visual-regression review server. Each tool maps to a distinct workflow step—finding builds, triaging results, paging stories, fetching images, and recording reviews—without redundant or bloated additions.

Completeness5/5

The tool surface covers the full UI-verification loop: discover builds, inspect gate verdicts, page through changed/failed/unchanged stories, fetch diff details and inline images, review individually or bulk-accept, and inspect PR-level visual changesets. No essential operation for the stated domain is missing.

Resources