Skip to main content
Glama

delimit_story_visual_test

Run visual regression tests by comparing screenshots against a stored baseline. Auto-creates baseline on first run; subsequent runs detect unintended visual changes.

Instructions

Run visual regression test — screenshot vs stored baseline.

When to use: as a CI gate after UI changes, to catch unintended visual regressions vs a stored baseline. Auto-creates the baseline on first run. When NOT to use: for a11y checks (use delimit_story_accessibility) or one-off screenshots (delimit_screenshot).

Sibling contrast: delimit_screenshot is one image without baseline; delimit_story_accessibility audits HTML; this compares against a stored baseline.

Side effects: writes baseline images on first run; subsequent runs are read-only against the baseline. Falls back to Puppeteer (screenshot only) when Playwright is not installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to screenshot.
project_pathNoProject path for baseline storage.
thresholdNoDiff threshold (0.0-1.0). Default 0.05.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Details side effects (writes baseline on first run, subsequent runs read-only) and fallback behavior (Puppeteer when Playwright missing). With no annotations provided, the description fully compensates by disclosing important behavioral traits.

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?

Compact and well-organized: a one-sentence summary followed by use/when-not, sibling contrast, and side effects. Every sentence adds value without redundancy.

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 tool has an output schema (documenting return values), the description covers usage guidelines, behavioral side effects, and sibling differentiation. It is sufficiently complete for an agent to correctly invoke the tool.

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 coverage is 100% with clear parameter descriptions and defaults (threshold default 0.05, project_path nullable). The description adds no extra parameter context beyond the schema, so baseline 3 is appropriate.

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 runs a visual regression test (screenshot vs. stored baseline). It distinguishes from siblings like delimit_screenshot (one-off screenshot) and delimit_story_accessibility (a11y/HTML audit), making its purpose precise and unique.

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?

Explicitly provides when to use (as a CI gate after UI changes) and when not to use (a11y checks, one-off screenshots), with direct references to alternative tools. This leaves no ambiguity for the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/delimit-ai/delimit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server