dogfood

dogfood is a skill for Claude Code, Codex from StarryCod/cogitum. It costs 18 tokens per session (1,447 once invoked), scanned A, a copy of dogfood, MIT.

A guided process for testing a web application by using it like a real user and looking for problems. It captures screenshots and other evidence, then produces a structured bug report.

In plain words
What is it for?
Use it to test a website or web app from a supplied URL and scope, including pages, features, browser output, and visual behavior.
Why use it?
It gives exploratory testing a repeatable process and preserves proof of each issue found. This helps developers reproduce and fix bugs.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/starrycod/cogitum/dogfood
Any agent
npx skills add StarryCod/cogitum --skill dogfood
Clone the repo
git clone --depth 1 https://github.com/StarryCod/cogitum

Made for: Claude Code, Codex.

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 dogfood

README.md
[![agentmods](https://agentmods.dev/badge/skills/starrycod/cogitum/dogfood.svg)](https://agentmods.dev/skills/starrycod/cogitum/dogfood)
Your own site
<a href="https://agentmods.dev/skills/starrycod/cogitum/dogfood"><img src="https://agentmods.dev/badge/skills/starrycod/cogitum/dogfood.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,447 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 92% copy Near-identical to another mod 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 $0.00018 $0.01447
Opus 5 $0.00009 $0.00724
Sonnet 5 $0.00004 $0.00289
Haiku 4.5 $0.00002 $0.00145

Measured 5d ago against content hash e2ff089820c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

dogfood scanned grade A with 0 findings 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 5d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

92% identical to dogfood — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

cogitum/data/skills/dogfood/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dogfood: Systematic Web Application QA Testing

Overview

This skill guides you through systematic exploratory QA testing of web applications using the browser toolset. You will navigate the application, interact with elements, capture evidence of issues, and produce a structured bug report.

Prerequisites

  • Browser toolset must be available (browser_navigate, browser_snapshot, browser_click, browser_type, browser_vision, browser_console, browser_scroll, browser_back, browser_press)
  • A target URL and testing scope from the user

Inputs

The user provides:

  1. Target URL — the entry point for testing
  2. Scope — what areas/features to focus on (or "full site" for comprehensive testing)
  3. Output directory (optional) — where to save screenshots and the report (default: ./dogfood-output)

Workflow

Follow this 5-phase systematic workflow:

Phase 1: Plan

  1. Create the output directory structure:
    {output_dir}/
    ├── screenshots/       # Evidence screenshots
    └── report.md          # Final report (generated in Phase 5)
    
  2. Identify the testing scope based on user input.
  3. Build a rough sitemap by planning which pages and features to test:
    • Landing/home page
    • Navigation links (header, footer, sidebar)
    • Key user flows (sign up, login, search, checkout, etc.)
    • Forms and interactive elements
    • Edge cases (empty states, error pages, 404s)

Phase 2: Explore

For each page or feature in your plan:

  1. Navigate to the page:

    browser_navigate(url="https://example.com/page")
    
  2. Take a snapshot to understand the DOM structure:

    browser_snapshot()
    
  3. Check the console for JavaScript errors:

    browser_console(clear=true)
    

    Do this after every navigation and after every significant interaction. Silent JS errors are high-value findings.

  4. Take an annotated screenshot to visually assess the page and identify interactive elements:

    browser_vision(question="Describe the page layout, identify any visual issues, broken elements, or accessibility concerns", annotate=true)
    

    The annotate=true flag overlays numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands.

Read the full file on GitHub · 163 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. 5d ago First seen · 163 lines · 18 tokens per session scan A e2ff089820c0

Subscribe to this mod's changes

dogfood is a skill published in the GitHub repository StarryCod/cogitum (11 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 1,447 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to dogfood, differing in 4 lines, and is treated as a copy.

Related

Other skills, from other repositories

smoke-test

End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke…

bytedance/deer-flow · 0 tokens

langbot-testing

Test LangBot WebUI and core product flows with an automated browser and backend logs. Use when validating the configured LangBot frontend, pipeline Debug Chat, model provider setup and test buttons, bot and knowledge-base UI flows, or troubleshooting failed LangBot end-to-end tests.

langbot-app/LangBot · 58 tokens

sanity-check

Run the deferred AgentOS E2E smoke test from public npm packages. Use when the user asks to sanity check, smoke test, or verify a release works.

rivet-dev/agentos · 37 tokens

penguin-harness-manual-test

Use when standing PenguinHarness up to try a change by hand — launching the Web App, the desktop shell, the landing page or the docs site to click through it, screenshot it, or reproduce a report. Covers the four dev entry points and their ports, which data root each writes to, and the four ways a healthy setup looks…

Prism-Shadow/penguin-harness · 77 tokens

gigacode-api-sanity

Compare GigaCode's OpenCode-compatible HTTP/SSE API with native OpenCode in isolated temporary workspaces. Use when asked to sanity-check, re-test, or manually validate Claude Sonnet streaming, multi-turn sessions, tool calls, permissions, file edits, cancellation, or post-cancel reuse.

rivet-dev/agentos · 67 tokens

local-test

Build, run, and test IronClaw locally using Docker containers and Chrome MCP browser automation.

suyoumo/ClawProBench · 22 tokens