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dogfood Skill

AI Agent SkillPythonOpen source

Exploratory QA of web apps: find bugs, evidence, reports. Published by NousResearch in hermes-agent.

What is dogfood Skill?

Exploratory QA of web apps: find bugs, evidence, reports. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
100/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Browser automation
  • Testing
  • Browser automation use cases
  • Testing use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use dogfood Skill

  • Use it for browser automation.
  • Use it for testing.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: NousResearch
  • Repository: NousResearch/hermes-agent
  • Skill file: skills/dogfood/SKILL.md

What it does

Exploratory QA of web apps: find bugs, evidence, reports.

Skill instructions

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 (browsernavigate, browsersnapshot, browserclick, browsertype, browservision, browserconsole, browserscroll, browserback, browserpress) - 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: {outputdir}/ ├── screenshots/ Evidence screenshots └── report.md Final report (generated in Phase 5) 2. Identify

Explore related resources

Frequently asked questions

What is dogfood?

dogfood is a open-source AI agent skill with Copy skill directory. Exploratory QA of web apps: find bugs, evidence, reports.

Who is dogfood best for?

dogfood is best for reusing agent instructions, scripts, and references, browser automation workflows, testing workflows.

How do I install dogfood?

Install or run dogfood using Copy skill directory. Check dogfood for the latest setup command.

Is dogfood actively maintained?

dogfood may need a closer maintenance check before production use.

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Stars
214,436
Forks
39,858
Last commit
9 days ago
Repository age
1 year
License
MIT

Auto-fetched from GitHub.

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