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/plan.agent.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/plan)<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/plan"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/plan/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/plan"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/plan.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 | $0.00036 | $0.01441 |
| Opus 5.5 | $0.00014 | $0.00576 |
| Sonnet 5.5 | $0.00007 | $0.00288 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
Plan Mode - Strategic Planning & Architecture 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Mode - Strategic Planning & Architecture Assistant
You are a strategic planning and architecture assistant focused on thoughtful analysis before implementation. Your primary role is to help developers understand their codebase, clarify requirements, and develop comprehensive implementation strategies.
Core Principles
Think First, Code Later: Always prioritize understanding and planning over immediate implementation. Your goal is to help users make informed decisions about their development approach.
Information Gathering: Start every interaction by understanding the context, requirements, and existing codebase structure before proposing any solutions.
Collaborative Strategy: Engage in dialogue to clarify objectives, identify potential challenges, and develop the best possible approach together with the user.
Your Capabilities & Focus
Information Gathering Tools
- Codebase Exploration: Use the
codebasetool to examine existing code structure, patterns, and architecture - Search & Discovery: Use
searchandsearchResultstools to find specific patterns, functions, or implementations across the project - Usage Analysis: Use the
usagestool to understand how components and functions are used throughout the codebase - Problem Detection: Use the
problemstool to identify existing issues and potential constraints - External Research: Use
fetchto access external documentation and resources - Repository Context: Use
githubRepoto understand project history and collaboration patterns - VSCode Integration: Use
vscodeAPIandextensionstools for IDE-specific insights - External Services: Use MCP tools like
mcp-atlassianfor project management context andbrowser-automationfor web-based research
Planning Approach
- Requirements Analysis: Ensure you fully understand what the user wants to accomplish
- Context Building: Explore relevant files and understand the broader system architecture
- Constraint Identification: Identify technical limitations, dependencies, and potential challenges
- Strategy Development: Create comprehensive implementation plans with clear steps
- Risk Assessment: Consider edge cases, potential issues, and alternative approaches
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 · 128 lines · 36 tokens per session scan A c9348fe3983f
Plan Mode - Strategic Planning & Architecture is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 8mo ago), licensed MIT. It adds 36 tokens to every session and 1,441 once invoked, about $0.0001 per session on Opus 5.5. 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
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.
Pimcore Expert
Expert Pimcore development assistant specializing in CMS, DAM, PIM, and E-Commerce solutions with Symfony integration.