Borrowing it
Nothing to install: this file belongs to HyunjunJeon/Deepagent-research-context-engineering. 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/HyunjunJeon/Deepagent-research-context-engineering/main/AGENTS.mdgit clone --depth 1 https://github.com/HyunjunJeon/Deepagent-research-context-engineeringWrote 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/instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md)<a href="https://agentmods.dev/instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md"><img src="https://agentmods.dev/badge/instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md/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/instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md"><img src="https://agentmods.dev/badge/instructions/hyunjunjeon/deepagent-research-context-engineering/agents-md.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 | $0.01052 | $0.01052 |
| Opus 5.5 | $0.00421 | $0.00421 |
| Sonnet 5.5 | $0.00210 | $0.00210 |
| Haiku 4.5 | $0.00105 | $0.00105 |
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 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 — 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)
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 · 123 lines · 1,052 tokens per session scan A 22a3dcf6b427
Deepagent-research-context-engineering AGENTS.md is an instructions file published in the GitHub repository HyunjunJeon/Deepagent-research-context-engineering (53 stars, last pushed 9mo ago), licensed MIT. It adds 1,052 tokens to every session, about $0.0042 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.
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