Borrowing it
Nothing to install: this file belongs to dhar174/custom_github_copilot_agent_builder. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dhar174/custom_github_copilot_agent_builder/main/.github/agents/agent-workflows.mdgit clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builderWrote 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.
[](https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/agent-workflows)<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/agent-workflows"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/agent-workflows/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.
<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/agent-workflows"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/agent-workflows.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.07461 |
| Opus 5.5 | $0.00000 | $0.02984 |
| Sonnet 5.5 | $0.00000 | $0.01492 |
| Haiku 4.5 | $0.00000 | $0.00746 |
Grade A, and why
agent-workflows 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 762 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This document visualizes the relationships between custom agents and defines logical workflow sequences for common development tasks.
Agent Ecosystem Overview
graph TB
subgraph "Planning & Design"
plan[Plan Mode]
architect[Architect]
prd[PRD Creator]
spec[Specification]
implplan[Implementation Plan]
end
subgraph "Implementation"
pse[Principal Software Engineer]
clean[Clean Code Agent]
debug[Debug Agent]
end
subgraph "Quality Assurance"
test[Test Writer]
security[Security Reviewer]
review[Code Reviewer]
end
subgraph "DevOps & Deployment"
devops[DevOps Expert]
ghactions[GitHub Actions Expert]
end
subgraph "Documentation"
refine[Refine Issue]
tech-content[Technical Content]
end
subgraph "Meta & Support"
foundry[Custom Agent Foundry]
mentor[Mentor]
research[Research & Spike]
end
classDef planning fill:#e1f5ff,stroke:#01579b,stroke-width:2px
classDef implementation fill:#f3e5f5,stroke:#4a148c,stroke-width:2px
classDef quality fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef devops fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px
classDef docs fill:#fce4ec,stroke:#880e4f,stroke-width:2px
classDef meta fill:#f1f8e9,stroke:#33691e,stroke-width:2px
class plan,architect,prd,spec,implplan planning
class pse,clean,debug implementation
class test,security,review quality
class devops,ghactions devops
class refine,tech-content docs
class foundry,mentor,research meta
Workflow 1: Feature Development (Complete Cycle)
Requirements
- REQ-001: All features must begin with planning and requirements documentation before implementation
- REQ-002: Technical specifications must be created from approved PRDs before architectural design
- REQ-003: Architecture decisions must be documented and reviewed before implementation planning
- REQ-004: Implementation must include automated tests with minimum 80% code coverage
- REQ-005: Security review must be performed before deployment
- REQ-006: DevOps deployment strategy must be defined and tested
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.
- 1mo ago First seen · 762 lines · 0 tokens per session scan A 49450bc28001
agent-workflows is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 7,461 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
process-automation
Maps a manual business process and automates the parts that should be automated — integrations, scheduled jobs, approvals, and the handoffs between them.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Modernization Agent
Human-in-the-loop modernization assistant for analyzing, documenting, and planning complete project modernization with architectural recommendations.