What is Agentflow copilot-instructions.md?

Repository-specific instructions for Agentflow, a Python framework for building workflows where multiple language-model agents perform connected steps. It documents the framework's graphs, state, messages, tools, and execution flow.

Use it when developing or maintaining Agentflow components such as workflow graphs, nodes, conditional routes, state models, and tool integrations.

It gives a coding agent the project's expected architecture and naming conventions before it changes or adds code.

How 10xHub/Agentflow configures GitHub Copilot

Reuse

Borrowing it

Nothing to install: this file belongs to 10xHub/Agentflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/10xHub/Agentflow/main/.github/copilot-instructions.md

Clone the repo

git clone --depth 1 https://github.com/10xHub/Agentflow

Made for: GitHub Copilot.

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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/10xhub/agentflow/copilot-instructions/github.svg)](https://agentmods.dev/instructions/10xhub/agentflow/copilot-instructions)

Your own site

<a href="https://agentmods.dev/instructions/10xhub/agentflow/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/10xhub/agentflow/copilot-instructions/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/10xhub/agentflow/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/10xhub/agentflow/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,587 This file is loaded in full into every session.

When invoked 1,587 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.01587	$0.01587
Opus 5.5	$0.00635	$0.00635
Sonnet 5.5	$0.00317	$0.00317
Haiku 4.5	$0.00159	$0.00159

Measured 2mo ago against content hash 0d4dc2b48bfd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Agentflow copilot-instructions.md 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 2mo 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.

.github/copilot-instructions.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot instructions for 10xScale Agentflow

Use these repo-specific notes to be productive quickly when generating code, docs, or tests.

Big picture

10xScale Agentflow is a lightweight Python framework for building multi-agent workflows with LLM-agnostic orchestration.
Core primitives live in agentflow/graph/: StateGraph, Node, Edge, ToolNode, CompiledGraph.
State is a Pydantic model (state/agent_state.py); messages are state/message.py::Message with multimodal content blocks (state/message_block.py).
Flow: build a StateGraph → add nodes/edges (incl. conditional) → set_entry_point → compile() → use CompiledGraph.invoke() or CompiledGraph.stream().
START/END constants come from utils/constants.py (START="__start__", END="__end__"). Always reference these.

Architecture essentials

Graph API (see graph/state_graph.py, graph/compiled_graph.py, graph/node.py):
- add_node(name, func|ToolNode), add_edge(from, to), add_conditional_edges(from, condition, path_map).
- compile(checkpointer, interrupt_before, interrupt_after) wires DI (InjectQ), checkpointer, callbacks, publisher; default checkpointer is in-memory.
Node contracts (graph/node.py):
- Functions accept (state: AgentState, config: dict, …deps) and return updated state, list[Message], or ModelResponseConverter.
- Streaming supported by .stream(...) and EventModel chunks.
Tools via ToolNode (graph/tool_node/base.py):
- Register plain callables or integrate MCP, Composio, LangChain. Get tool specs via await tool_node.all_tools().
- Tool functions may declare injectable params like tool_call_id and state (see examples).
- Supports parallel tool execution.
Persistence & events:
- Checkpointers: InMemoryCheckpointer (default) and PgCheckpointer (Postgres+Redis, extras required).
- Publishers emit execution events (ConsolePublisher for dev). Events are publisher/events.py::EventModel.
State management:
- AgentState has context (list of messages with add_messages reducer), context_summary, and execution_meta (internal execution state).
- Subclass AgentState to add custom fields while maintaining framework compatibility.
- Use BaseContextManager for custom context trimming logic.

Read the full file on GitHub · 81 lines

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.

2mo ago Changed · +3 lines · +67 tokens per session 0d4dc2b48bfd
2mo ago First seen · 78 lines · 1,520 tokens per session scan A 4a5f3ae51914

Subscribe to this mod's changes

Agentflow copilot-instructions.md is an instructions file published in the GitHub repository 10xHub/Agentflow (21 stars, last pushed 1mo ago), licensed MIT. It adds 1,587 tokens to every session, about $0.0063 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 2026-08-30.

Building agents agent-framework agentic-ai ai-agents ai-agents-framework anthropic google-genai

Agentflow copilot-instructions.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
Agentflow copilot-instructions.md10xHub/Agentflow	Instructions file	21	1mo ago	MIT	A	1,587	GitHub Copilot
agentforge-py copilot-instructions.mdScaffoldic/agentforge-py	Instructions file	10	1mo ago	Apache-2.0	A	101	GitHub Copilot
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot

Agentflow: Instructions file for GitHub Copilot