autoqa

autoqa is a skill for Claude Code from Parcha-ai/parcha-skills. It costs 93 tokens per session (2,409 once invoked), scanned A, original, MIT.

An end-to-end quality-checking workflow for a repository's running application. It tests the live app and records evidence such as responses, screenshots, logs, or database rows.

In plain words
What is it for?
Use it to discover how an app runs, test its features through different interaction types, and produce a witnessed pass-or-fail report.
Why use it?
It replaces assumptions based on files existing with checks that show whether the application's features actually work.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool; mentions AGENTS.md.

Part of the autoqa plugin — 1 skill shipped together

Good fit Use it to discover how an app runs, test its features through different interaction types, and produce a witnessed pass-or-fail report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parcha-ai/parcha-skills/autoqa
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Parcha-ai/parcha-skills --skill autoqa
Clone the repo
git clone --depth 1 https://github.com/Parcha-ai/parcha-skills

Made for: Claude Code.

Or install autoqa, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for autoqa

README.md
[![agentmods](https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/autoqa/github.svg)](https://agentmods.dev/skills/parcha-ai/parcha-skills/autoqa)
Your own site
<a href="https://agentmods.dev/skills/parcha-ai/parcha-skills/autoqa"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/autoqa/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for autoqa

Your own site · 80×15
<a href="https://agentmods.dev/skills/parcha-ai/parcha-skills/autoqa"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/autoqa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,409 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.02409
Opus 5 $0.00046 $0.01205
Sonnet 5 $0.00019 $0.00482
Haiku 4.5 $0.00009 $0.00241

Measured 10d ago against content hash d6fe2feeebd9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

autoqa scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

they resolve. Name witness files by row: curl output with status codes, page snapshots or
autoqa/skills/autoqa/SKILL.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

autoqa — QA any repo against its own running app

You are the QA engineer for this repo. Every verdict is witnessed — it points at an artifact (an HTTP response, a page snapshot, a log line, a DB row) that shows the result, not merely a file that exists. The full witness contract is in Hard rules below.

Phase 0 — RESOLVE

Establish three facts before anything else:

  1. Target repo — path or URL the user pointed at (ask only if truly absent).
  2. Target instance — a running deployment to test against (URL/port), or the instruction to bring one up locally.
  3. Repo config — look for AUTOQA.md at the repo root or under docs/. It is the repo's reusable baseline, not the complete plan: how to run, how to auth, stable catalog/core checks, and known env caveats. If found, read it now and skip the generic discovery in Phase 1, but never skip Phase 2's diff discovery. Missing config means full Phase 1 — and a repo you QA repeatedly earns one: write AUTOQA.md from what Phase 1 taught you so later runs can start from that baseline.

Done when: repo path, instance URL (or "must boot"), and config-or-none are stated.

Phase 1 — DISCOVER

Read the repo the way a new engineer would, in this order, stopping when the three questions below are answered. Full source-priority list and what each source answers: references/discovery.md.

  • How does it run? Dockerfile / compose / Procfile / Makefile / CI workflows / README.
  • How do I authenticate? env samples, auth middleware, dev-token conventions, CLAUDE.md / AGENTS.md.
  • What are the features? a feature catalog or spec doc if the repo ships one (use it — it beats inference), else routes/pages/CLI entrypoints enumerated from code.

Done when: you can write down the run command, an auth recipe, and a feature inventory — each traced to the file that taught you it.

Phase 2 — PLAN

Build the plan from the union of two sources:

  1. Baseline inventory — every feature/check required by AUTOQA.md, or Phase 1 when no config exists.
  2. Diff inventory — cases derived from the actual change under test. Resolve the base from the user's target or PR; otherwise use the merge-base with the repository's default remote branch. Include committed, staged, unstaged, and relevant untracked changes. Read the diff and the acceptance/design docs it changes or cites. Derive behavior-level cases for changed user entry points, APIs/contracts, schemas/migrations, background work, configuration and feature flags, compatibility/fallbacks, failure handling, security or authorization boundaries, concurrency/idempotency, rollout/rollback, and cleanup. Do not mistake a large unit-test list for this inventory.

Read the full file on GitHub · 169 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 169 lines · 93 tokens per session scan A d6fe2feeebd9

Subscribe to this mod's changes

autoqa is a skill published in the GitHub repository Parcha-ai/parcha-skills (59 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 2,409 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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