Deepagent-research-context-engineering AGENTS.md

Deepagent-research-context-engineering AGENTS.md is an instructions file for Codex, OpenCode from HyunjunJeon/Deepagent-research-context-engineering. It costs 1,052 tokens per session, scanned A, original, MIT.

Project instructions for a research system that uses several AI agents to gather and organize information. The project includes Python, Rust, and Next.js components, where Next.js is a framework for building web applications.

In plain words
What is it for?
Use them when modifying the research orchestrator, adding research tools, working on the web interface or Rust implementation, or locating tests and project documentation.
Why use it?
They give the agent a map of the project, including where the orchestrator, research tools, user interface, tests, and supporting code are located.

Instructions file for CodexOpenCode

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 instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md
Clone the repo
git clone --depth 1 https://github.com/HyunjunJeon/Deepagent-research-context-engineering

Made for: Codex, OpenCode.

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README.md
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Per session 1,052 This file is loaded in full into every session.
When invoked 1,052 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.01052 $0.01052
Opus 5 $0.00526 $0.00526
Sonnet 5 $0.00210 $0.00210
Haiku 4.5 $0.00105 $0.00105

Measured 4d ago against content hash 22a3dcf6b427, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Deepagent-research-context-engineering AGENTS.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 4d 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.

AGENTS.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PROJECT KNOWLEDGE BASE

Generated: 2026-01-13


OVERVIEW

Multi-agent research system demonstrating FileSystem-based Context Engineering using LangChain's DeepAgents framework. Includes Python orchestrator, Rust port via Rig framework, and Next.js chat UI.


STRUCTURE

/
  research_agent/          # Python DeepAgent orchestrator (see AGENTS.md)
  context_engineering_research_agent/  # Extended agent with 5 strategies
  deep-agents-ui/          # Next.js React frontend (see AGENTS.md)
  rust-research-agent/     # Rust implementation (see AGENTS.md)
    rig-deepagents/        # Pregel-based middleware runtime
    rig-rlm/               # Recursive Language Model agent
  tests/                   # pytest test suite (see AGENTS.md)
  skills/                  # Project-level skills (SKILL.md per skill)
  research_workspace/      # Agent output directory (ephemeral)
  deepagents_sourcecode/   # Vendor: upstream library reference

WHERE TO LOOK

Task Location Notes
Modify orchestrator research_agent/agent.py SubAgent assembly, tools, middleware
Add research tool research_agent/tools.py tavily_search, think_tool
Autonomous researcher logic research_agent/researcher/ Three-phase workflow
Context strategies context_engineering_research_agent/context_strategies/ 5 patterns
Frontend components deep-agents-ui/src/app/components/ Chat UI
Rust Pregel runtime rust-research-agent/rig-deepagents/src/pregel/ Graph execution
Rust middleware rust-research-agent/rig-deepagents/src/middleware/ Tool injection
Add new skill skills/{skill-name}/SKILL.md YAML frontmatter + instructions

CONVENTIONS

Deviations from Standard Patterns

  • Backend factory pattern: Always use backend_factory(rt: ToolRuntime) - middleware depends on this signature
  • SubAgent naming: Use researcher, explorer, synthesizer - hardcoded in prompts
  • File paths: Paths starting with "/" route to research_workspace/; others are in-memory
  • Korean comments: Docstrings and some comments in Korean (bilingual codebase)

Read the full file on GitHub · 123 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.

  1. 4d ago First seen · 123 lines · 1,052 tokens per session scan A 22a3dcf6b427

Subscribe to this mod's changes

Deepagent-research-context-engineering AGENTS.md is an instructions file published in the GitHub repository HyunjunJeon/Deepagent-research-context-engineering (53 stars, last pushed 7mo ago), licensed MIT. It adds 1,052 tokens to every session, about $0.0053 per session on Opus 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.