UI Verify

Accept, deny, or ignore one story's change

review_diff

Record a review on a single diff result (get diffResultId from get_build/get_diff). 'accept' makes the candidate the new baseline for that story on its branch, so the next build is clean; 'deny' records the rejection without changing the baseline; 'ignore' excludes the story from the gate persistently (the snapshot keeps differing on future builds but no longer flags the check) — use it for an intentional, ongoing diff like an animation or a live timestamp. This is the same accept/deny/ignore as the dashboard, attributed to your project key. Use after you've inspected the diff (e.g. with render_diff_image) and decided intended vs. regression.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`decision`	Yes	'accept' advances the baseline; 'deny' records a rejection; 'ignore' excludes the story from the gate.
`diffResultId`	Yes	The diff result id from get_build or get_diff.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`decision`	Yes
`diffResultId`	Yes

Schema Changelog

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

Changed1 schema field changedSep 5, 2026

changedOutput schema / (root)

Before

null

After

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "additionalProperties": false,
  "properties": {
    "decision": {
      "enum": [
        "accepted",
        "denied",
        "ignored"
      ],
      "type": "string"
    },
    "diffResultId": {
      "format": "uuid",
      "type": "string"
    }
  },
  "required": [
    "diffResultId",
    "decision"
  ],
  "type": "object"
}

First observedSep 5, 2026

TDQS

A4.8/5.0

Behavior5/5

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

The description explains the persistent side effects of each option: accepting advances the baseline, denying records a rejection without changing baseline, and ignoring permanently excludes the story from the gate while the snapshot continues to differ. It also notes attribution to the project key and the impact on the next build, going well beyond the minimal annotations.

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 but every sentence contributes essential decision-making information. It is front-loaded with the action and source of diffResultId, and the decision semantics are clearly separated. Slightly long, but the length is justified by the three distinct behaviors that must be explained.

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?

Given the presence of an output schema, the two-parameter input schema, and the rich descriptions, the description covers prerequisites, decision semantics, persistence, and attribution. An agent has enough context to call this tool correctly and understand the consequences of each choice.

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 coverage is 100%, so the baseline is 3. The description adds meaningful semantics on top by explaining how to get diffResultId ('from get_build/get_diff') and by detailing the downstream effects of each decision value, which helps the agent choose the correct enum value in context.

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 action ('Record a review') on a concrete resource ('a single diff result') and enumerates the three decision semantics. It clearly distinguishes itself from inspection and retrieval siblings like render_diff_image and get_diff by focusing on the post-inspection review action.

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 explicitly says to use this after inspecting the diff (e.g., with render_diff_image) and after deciding whether the change is intended or a regression. It also clarifies that 'ignore' is for intentional, ongoing diffs, giving concrete when-to-use guidance that routes the agent correctly.

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

Disambiguation5/5

Each tool targets a distinct concern: list vs get vs pagination, build triage vs PR changeset, diff URL vs inline pixels, single-review vs bulk-accept. The descriptions explicitly call out the differences between similar-sounding tools, so an agent can reliably choose the right one.

Naming Consistency5/5

All tool names follow a consistent lowercase verb_noun pattern: get_* for single entities, list_* for collections, and review_diff/accept_build for actions. There are no mixed conventions or vague verbs.

Tool Count5/5

Nine tools fit the visual regression review workflow well: discovery, triage, pagination, image inspection, and reviewing. Each tool fills a distinct role without redundancy, and the count is in the sweet spot for an agent to keep all tool purposes in context.

Completeness5/5

The surface covers the full review lifecycle: find builds, triage changed/failed/unchanged stories, paginate, inspect diffs as URLs or inline images, review per-diff, and bulk-accept an entire build. The PR-changeset tools also cover cross-PR questions and deletion cases that would otherwise be dead ends.

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