Official agent skill

Dotagents QA

by getsentry in getsentry/dotagents

QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections.

OfficialMITAuto-check passedDevOps & Cloud

Install Dotagents QA

skills CLI
$ npx skills add getsentry/dotagents --skill dotagents-qa -a claude-code

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

GitHub CLI
$ gh skill install getsentry/dotagents dotagents-qa --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/getsentry/dotagents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dotagents-qa .claude/skills/dotagents-qa && 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
dotagents-qa
GitHub stars
247
Token cost
~1.9k tokens
SKILL.md length
887 words
Files
27 (incl. scripts, references)
Skills in repo
3
Repo updated
First seen
Licence
MIT

At a glance

QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections.

  • Works in 7 steps: Define the contract → Establish isolation → Run baseline validation → …
  • Harness integration needs runtime proof
  • SKILL.md covers 1. Define the contract, 2. Establish isolation, 3. Run baseline validation and 4. Exercise complete lifecycles, plus 3 more sections
  • Calls pnpm and opencode

What it does

Dotagents QA is an agent skill from getsentry/dotagents, published by the product's own GitHub organization. QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections. Use when behavior, packaging, scopes, or harness integration needs runtime proof.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 29 other files, including scripts and reference files (for example `SOURCES.md`, `evals/cases/define-the-qa-contract.yaml` and `evals/cases/enforce-docker-isolation.yaml`).

It sits in DevOps & Cloud, covering Containers. It works with Docker. The licence is MIT.

When your agent uses it

  • Harness integration needs runtime proof
  • Tasks that involve Containers

Example prompts

  • “/dotagents-qa”

Requirements

  • Docker

Workflow steps

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

  1. Define the contract
  2. Establish isolation
  3. Run baseline validation
  4. Exercise complete lifecycles
  5. Test representative plugins
  6. Prove harnesses independently
  7. Report

What it can do on your machine

Read from SKILL.md and the folder at commit 75a89fd. 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

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • pnpm
    • opencode

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

  • Network

    No URLs in SKILL.md. Its commands use pnpm, 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

Dotagents QA loads about 1.9k tokens when it runs, and up to ~9.9k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 887 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.9k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from getsentry/dotagents at commit 75a89fd, republished under its MIT licence (© getsentry). 887 words, ~1,949 tokens.

Download SKILL.mdSave it as .claude/skills/dotagents-qa/SKILL.md (or your agent's skills folder). This skill also uses 26 other files; get the full folder from GitHub.
name
dotagents-qa
description
QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections. Use when behavior, packaging, scopes, or harness integration needs runtime proof.
spec_hash
eda48b96deb3

dotagents QA

Prove the requested behavior in Docker without touching host agent homes, caches, plugin registries, or credentials. Treat Docker as the safety boundary and the changed or released behavior as the test plan.

1. Define the contract

Before commands, state:

  • the exact subject: local checkout, packed local build, or published version;
  • the commands and semantics at risk;
  • default-global scope, explicit-project scope, or both;
  • the harnesses involved;
  • the fixture and evidence that constitute a pass.

For a published release, verify its registry metadata and install that exact version. Never silently test the local checkout instead. If you fix a discovered defect, report the release failure and packed-local-build pass separately.

Read the relevant references before acting:

Planning is part of acting: read the relevant references before proposing a command sequence, not only before executing it.

2. Establish isolation

Use the repo QA image. Rebuild it when the Dockerfile, pnpm version, or required current harness versions changed.

Run package and runtime work as a non-root user. Keep these inside Docker or disposable directories:

bash
export HOME=/sandbox/home
export DOTAGENTS_STATE_DIR=/sandbox/state
export DOTAGENTS_HOME=/sandbox/user-agents
export COPILOT_HOME=/sandbox/copilot-home
export CODEX_HOME=/sandbox/codex-home
export CLAUDE_CONFIG_DIR=/sandbox/claude-home

Mount the host checkout read-only and copy it into the container without .git, node_modules, dist, coverage, or *.tsbuildinfo. Never point user-scope commands or client CLIs at the host's real home.

Do not forward auth for file, validation, marketplace, or resource-discovery checks. Copy credentials only for a separately authorized model-backed proof, scrub them afterward, and never retain them in /qa-out.

3. Run baseline validation

For a local plugin/runtime change, normally run:

bash
pnpm install --frozen-lockfile
pnpm check
pnpm qa:example
pnpm qa:plugins

Add focused regression tests for every confirmed logic bug. A failing baseline is a finding; do not bypass it silently. If a check is irrelevant or unavailable, record why.

4. Exercise complete lifecycles

Use the CLI from a fresh fixture and inspect output plus files:

bash
dotagents --project init --agents claude,codex,opencode,pi
dotagents --project add <source> [name]
dotagents --project list --json
dotagents --project doctor
dotagents --project install

Inspect agents.toml, agents.lock, canonical skills/plugins, ownership markers, marketplaces, manifests, harness projections, and warnings. Delete representative managed artifacts, run dotagents --project sync, and prove exact repair. Run dotagents --project remove <name> and prove canonical and generated cleanup.

Invoke every lifecycle command named by the contract with the intended scope. In particular, run install explicitly even though add also installs, and assert the config and lockfile paths directly rather than inferring them from list output.

For scope-selection changes, create both a project config and isolated global config, then prove unqualified commands mutate only global state from inside that configured repository. Prove --project mutates only project state, both --global and --user select the global paths, --global --user executes once, and either alias combined with --project fails before creating or changing files. Also cover --project init outside Git.

Test hook migration explicitly: create an executable, marker-delimited legacy post-merge hook containing unrelated lines around the bare install command; prove --project doctor diagnoses it and --project doctor --fix changes only the managed command to explicit project scope while preserving the unrelated content and executable mode.

Cover an unambiguous skill source as well as plugins so plugin-first discovery still falls back correctly. Use --all only with a controlled small catalog.

For global plugins, test the unqualified default plus both --global and legacy --user. Isolate HOME and DOTAGENTS_HOME; inspect global Claude, Codex, OpenCode, and Pi paths; repair with one spelling and remove with another.

Show full SKILL.md (326 more words)Show less

5. Test representative plugins

When plugin compatibility is in scope, inspect current manifests and test:

  • getsentry/agent-plugin;
  • vercel/vercel-plugin;
  • one high-signal plugin selected from the current manifest in anthropics/claude-plugins-official.

In a proposed compatibility plan, name all three repositories but defer the Anthropic plugin selector until manifest inspection at execution time. Derive all selectors, versions, commits, and component counts from that inspection.

Use a fresh project per source. Record source commits. Do not guess repository names, selectors, versions, component counts, or layouts.

6. Prove harnesses independently

Keep per-harness fixtures isolated. In particular, do not enable Pi in the OpenCode proof: OpenCode can read Pi's shared .agents/skills links and create a false pass.

  • Claude: validate generated plugin and marketplace manifests, then marketplace add, install, list, and details.
  • Copilot: add the generated marketplace, browse it, install the plugin, and list the installed plugin.
  • Codex: add the project or user marketplace root, list available plugins, install, and list enabled plugins.
  • OpenCode: run opencode debug skill and opencode debug config; assert exact projected skill names and locations plus every portable plugin MCP entry under plugin.<plugin>.<server> with expanded paths and environment.
  • Pi: in a separate Pi-only fixture, verify expected skill links, resolved targets, and .dotagents-managed/<skill> ownership markers.

These no-auth checks prove validation, registration, installation, or resource discovery. They do not prove model-backed invocation. Never claim a plugin skill or subagent executed without a model interaction and visible evidence.

7. Report

Include:

  • exact dotagents and harness versions;
  • Docker image/setup and non-root user;
  • fixture shapes and source commits;
  • commands and inspected paths;
  • assertions that passed;
  • confirmed defects and their regression tests;
  • release results versus local-fix results;
  • skipped authenticated checks and residual risk;
  • retained /qa-out location, if any.

Reporting is lossless. Enumerate every supplied command, version, source commit, and inspected path, even when repetitive. A category summary such as “state and marketplaces” is insufficient; do not invent missing values.

Keep the report candid: filesystem proof, native management proof, resource-discovery proof, and model-backed execution are different confidence levels.

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

Files

SKILL.md and 26 other files (scripts, references) in skills/dotagents-qa of getsentry/dotagents.

  • SKILL.md
  • Dockerfile
  • SOURCES.md
  • evals/cases/define-the-qa-contract.yaml
  • evals/cases/enforce-docker-isolation.yaml
  • evals/cases/exercise-complete-cli-lifecycles.yaml
  • evals/cases/prove-each-harness-independently.yaml
  • evals/cases/report-evidence-and-limits.yaml
  • evals/cases/run-proportionate-baseline-validation.yaml
  • evals/cases/test-representative-real-plugins.yaml
  • evals/cases/verify-project-scope-migration-edges.yaml
  • evals/cases/verify-scope-flag-compatibility.yaml
  • evals/cases/verify-scope-reversal-release.yaml
  • references/claude.md
  • references/codex.md
  • references/copilot.md
  • references/core-agentic-qa.md
  • references/cursor.md
  • … and 9 more

Open the folder on GitHubat commit 75a89fd

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Works with

Categories

Questions about Dotagents QA

What does Dotagents QA do?

QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections. Dotagents QA is an agent skill from getsentry/dotagents, published by the product's own GitHub organization. QA dotagents changes and published releases in Docker, including CLI lifecycles, user/global scope, real plugins, and Claude, Copilot, Codex, OpenCode, or Pi projections.

When should I use Dotagents QA?

Dotagents QA fits situations like: harness integration needs runtime proof; tasks that involve Containers.

How do I install Dotagents QA in Claude Code?

Run `npx skills add getsentry/dotagents --skill dotagents-qa -a claude-code`. Or copy the skill folder (skills/dotagents-qa in getsentry/dotagents) into .claude/skills/dotagents-qa in your project. Claude Code loads it when a task matches its description.

How do I install Dotagents QA in Codex?

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

Can I use Dotagents QA 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 getsentry/dotagents --skill dotagents-qa -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dotagents-qa, .gemini/skills/dotagents-qa, .github/skills/dotagents-qa and .opencode/skills/dotagents-qa in your project.

What does Dotagents QA need to run?

Going by SKILL.md and its folder, Dotagents QA needs the command-line tools its instructions call (pnpm and opencode). Our summary lists: Docker.

Does Dotagents QA access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Dotagents QA 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Dotagents QA use?

Dotagents QA 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 Dotagents QA use?

About 1.9k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.9k tokens, read only when the agent opens those files.

What are the alternatives to Dotagents QA?

Skills that share tags, products or a category with Dotagents QA: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 259 stars) and LangBot Deployment Guide (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dotagents QA?

getsentry (a GitHub organization, an official publisher) maintains it in getsentry/dotagents, which has 247 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 2, 2026.

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