Agent skill

Meticulous Test

by FlintSH in FlintSH/Flare

Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended.

MITAuto-check passedDevOps & Cloud

Install Meticulous Test

skills CLI
$ npx skills add FlintSH/Flare --skill meticulous-test -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FlintSH/Flare meticulous-test --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/FlintSH/Flare.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/meticulous-test .claude/skills/meticulous-test && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
meticulous-test
GitHub stars
135
Token cost
~1.2k tokens
SKILL.md length
520 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended.

  • Works in 4 steps: Build the frontend → Upload the build → Trigger a test run → …
  • Implementing a feature autonomously end-to-end before creating a PR
  • SKILL.md covers Step 1 -- Build the frontend, Step 2 -- Upload the build, Step 3 -- Trigger a test run and Step 4 -- Review the visual…
  • Calls npx and git

What it does

Meticulous Test is an agent skill from FlintSH/Flare. Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended. Uploads the build once — the same build can be re-triggered against different bases without rebuilding — and it works with uncommitted changes. Use when implementing a feature autonomously end-to-end before creating a PR.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud. It works with Docker, GitLab and Git. The repository describes itself as: A modern, lightning-fast file sharing platform built for self-hosting. Created with support for ShareX, KDE Spectacle, Flameshot, and easy to set up. The licence is MIT.

When your agent uses it

  • Implementing a feature autonomously end-to-end before creating a PR

Example prompts

  • “/meticulous-test”

Requirements

  • Node.js
  • Docker

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Build the frontend
  2. Upload the build
  3. Trigger a test run
  4. Review the visual changes

What it can do on your machine

Read from SKILL.md and the folder at commit c910523. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx and git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Meticulous Test loads about 1.2k tokens when it runs. Until then it costs about 102 tokens; SKILL.md has 520 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from FlintSH/Flare at commit c910523, republished under its MIT licence (© FlintSH). 520 words, ~1,228 tokens.

Download SKILL.mdSave it as .claude/skills/meticulous-test/SKILL.md (or your agent's skills folder).
name
meticulous-test
description
Run a Meticulous test run after implementing a frontend change, then hand off to the `meticulous-review` skill to classify each visual change as intended or unintended. Uploads the build once — the same build can be re-triggered against different bases without rebuilding — and it works with uncommitted changes. Use when implementing a feature autonomously end-to-end before creating a PR.
user-invocable
true

To test a frontend change using Meticulous, follow the workflow below step by step, using the CLI or MCP commands as described.

Before starting, run the meticulous-cli-update skill to ensure the Meticulous CLI and skills are up to date — unless it has already run earlier in this conversation, in which case skip it.

If you are already given a test run id, skip to Step 4.

Step 1 -- Build the frontend

  1. Find out what build artefact Meticulous expects by checking your CI config for the corresponding step:
    • GitHub: .github/workflows/*.yml for uses: alwaysmeticulous/report-diffs-action/upload-assets@v1 (build assets) or upload-container@v1 (docker image)
    • GitLab: .gitlab-ci.yml (or an included .gitlab/ci/*.yml) for npx @alwaysmeticulous/cli ci upload-assets (build assets) or ci upload-container (docker image)
    • Bitbucket: bitbucket-pipelines.yml for the same npx @alwaysmeticulous/cli ci upload-assets / ci upload-container step
  2. Build the frontend following the same instructions as used in that CI config.

Step 2 -- Upload the build

Register the build as a reusable deployment with agent upload-build. This uploads the artefact and prints a deploymentId to stdout — it does not trigger a run yet.

bash
# CLI
meticulous agent upload-build --appDirectory <path-to-build>     # assets
meticulous agent upload-build --localImageTag <image-tag>        # container

# MCP (not 1:1 — request an upload URL, upload the artifact yourself, then register it)
request_asset_upload(size=<zipByteSize>)      # or request_container_upload() — no required args
# ... upload the zip/image to the returned URL/registry yourself ...
register_asset_build(uploadId="<id>", commitSha="<sha>")      # or register_container_build(uploadId="<id>", commitSha="<sha>")
  • --appDirectory points to the build output directory (e.g. a dist/ subfolder); --localImageTag is the local Docker image tag. The build mode is auto-detected.
  • The build's commit defaults to the local git HEAD. If the working tree is dirty, it is captured as an ephemeral commit (printed as commitSha (local, ephemeral due to dirty working tree): …) — see the uncommitted-changes note below.
  • Untracked files are rejected (they can't be captured) — git add them first.
  • Capture the deploymentId from stdout (pass --verbose to also see progress on stderr).
Show full SKILL.md (260 more words)Show less

Step 3 -- Trigger a test run

Trigger a run for the deployment, comparing against a base. Run it from the repo directory to infer both the base (merge-base with the origin default branch) and the git diff automatically:

bash
# CLI
meticulous agent trigger-test-run --deploymentId <deploymentId>

# MCP (never infers `baseSha`/`gitDiffOutput` — pass them explicitly — and always returns immediately without waiting for the run to finish)
trigger_test_run(deploymentId="<deploymentId>", baseSha="<sha>")
  • A base is required. It's auto-inferred from the current directory, or pass --baseSha <sha> (and optionally --gitDiffOutput) to set it explicitly.
  • Omit --deploymentId to use the most recent deployment already uploaded for the local HEAD commit instead — this requires a clean working tree (no uncommitted changes).
  • The command blocks until the run finishes by default and prints the testRunId to stdout; the final status is Failure when visual differences were detected (a normal completed verdict, not an error). Pass --dontWaitForTestRunToComplete to return as soon as the run is triggered.
  • One build, many bases: the same deploymentId can be re-triggered against different bases — just run agent trigger-test-run again with a different --baseSha. No rebuild or re-upload needed.

Note the testRunId from the output.

Step 4 -- Review the visual changes

Follow the meticulous-review skill, passing the testRunId from Step 3. It fetches the diff summary, inspects representative screenshots / DOM diffs / timelines, and produces a final report classifying each visual change as intended or unintended.

Uncommitted changes: if you built/tested with a dirty working tree, the run is recorded against an ephemeral commit that is not your HEAD (and isn't pushed). Commands that resolve a run from the local checkout — meticulous-review / agent test-run-diffs run with no --testRunId — won't find it by commit, so always pass the explicit --testRunId to the review step in that case.

© FlintSH, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/meticulous-test of FlintSH/Flare.

Open the folder on GitHubat commit c910523

Compare with similar skills

Meticulous Test next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Meticulous Test compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Meticulous Test this skillFlintSH/Flare135—~1.2kAutomated safety check: PassMIT
Modern Web GuidanceJetBrains/skills3663 repos~1.4kAutomated safety check: PassApache-2.0
Ssh Skillbadseal/ssh-skill538—~2.4kAutomated safety check: NotesNone
Setup Osworldxlang-ai/OSWorld-V23591 repos~2.6kAutomated safety check: NotesApache-2.0
Crabbox Quickstartopenclaw/crabbox1.5k—~1.6kAutomated safety check: NotesMIT
Reviewwerf/werf4.7k—~2kAutomated safety check: PassApache-2.0

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Works with

Questions about Meticulous Test

What does Meticulous Test do?

Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended. Meticulous Test is an agent skill from FlintSH/Flare. Run a Meticulous test run after implementing a frontend change, then hand off to the meticulous-review skill to classify each visual change as intended or unintended.

When should I use Meticulous Test?

Meticulous Test fits situations like: implementing a feature autonomously end-to-end before creating a PR.

How do I install Meticulous Test in Claude Code?

Run `npx skills add FlintSH/Flare --skill meticulous-test -a claude-code`. Or copy the skill folder (.agents/skills/meticulous-test in FlintSH/Flare) into .claude/skills/meticulous-test in your project. Claude Code loads it when a task matches its description.

How do I install Meticulous Test in Codex?

Run `npx skills add FlintSH/Flare --skill meticulous-test -a codex`. Or copy the skill folder (.agents/skills/meticulous-test in FlintSH/Flare) into .agents/skills/meticulous-test in your project. Codex loads it when a task matches its description.

Can I use Meticulous Test in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FlintSH/Flare --skill meticulous-test -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meticulous-test, .gemini/skills/meticulous-test, .github/skills/meticulous-test and .opencode/skills/meticulous-test in your project.

What does Meticulous Test need to run?

Going by SKILL.md and its folder, Meticulous Test needs the command-line tools its instructions call (npx and git). Our summary lists: Node.js; Docker.

Does Meticulous Test access the network?

SKILL.md contains no URLs. Its commands use npx and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Meticulous Test safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Meticulous Test use?

Meticulous Test is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Meticulous Test use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Meticulous Test?

Skills that share tags, products or a category with Meticulous Test: Modern Web Guidance (JetBrains/skills, 366 stars), Ssh Skill (badseal/ssh-skill, 538 stars), Setup Osworld (xlang-ai/OSWorld-V2, 359 stars) and Crabbox Quickstart (openclaw/crabbox, 1.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meticulous Test?

FlintSH (a GitHub user) maintains it in FlintSH/Flare, which has 135 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 6, 2026.

Source: FlintSH/Flare on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.