Borrowing it
Nothing to install: this file belongs to geekjourneyx/industry-research. 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/geekjourneyx/industry-research/main/AGENTS.mdgit clone --depth 1 https://github.com/geekjourneyx/industry-researchWrote 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/geekjourneyx/industry-research/agents-md)<a href="https://agentmods.dev/instructions/geekjourneyx/industry-research/agents-md"><img src="https://agentmods.dev/badge/instructions/geekjourneyx/industry-research/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/geekjourneyx/industry-research/agents-md"><img src="https://agentmods.dev/badge/instructions/geekjourneyx/industry-research/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 | $0.01429 | $0.01429 |
| Opus 5 | $0.00714 | $0.00714 |
| Sonnet 5 | $0.00286 | $0.00286 |
| Haiku 4.5 | $0.00143 | $0.00143 |
Grade A, and why
industry-research 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 9d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file guides Codex work in this repository.
What This Is
This repository contains a Codex skill and a Go CLI for industry research.
The system takes a fuzzy industry, sector, company, or business-opportunity question and turns it into a structured research workspace and report. The core quality standard is evidence discipline: search results and model answers are only leads until they are verified against sources, operating traces, or cross-source checks.
The specialized restaurant, retail, supply-chain, and chain-brand path uses operating-trace verification instead of narrative-only market analysis.
Current Architecture
The current execution center is researcher, a Go CLI in researcher/.
SKILL.md is still the Codex entry point. It routes the request, chooses depth and domain, calls researcher, then uses the four agent role files as review and challenge layers.
The older pure prompt-only pipeline remains useful as a fallback and review model, but it is no longer the primary architecture.
Main Components
| Component | Path | Role |
|---|---|---|
| Skill entry | SKILL.md |
Codex-facing orchestration contract |
| CLI | researcher/ |
Builds workspaces, provider calls, trace planning, evidence ledger, confidence, validation |
| Engagement Manager | agents/engagement-manager.md |
Reviews claim graph and trace plan |
| Blue Team | agents/blue-team.md |
Reviews support evidence and upside thesis |
| Red Team | agents/red-team.md |
Searches for missing traces, conflicts, and over-claimed evidence |
| Chief Arbitrator | agents/chief-arbitrator.md |
Checks consistency among confidence, evidence, and final report |
| Validator | scripts/validate_report.py |
Validates report shape and researcher workspace artifacts |
Primary Flow
- User asks for
/industry-researchor an equivalent industry research task. SKILL.mddetermines language, depth, and domain.- The skill calls:
researcher run "<question>" --domain <domain> --depth <brief|standard|comprehensive> --workspace-root <workspace_root>
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.
- 9d ago First seen · 162 lines · 1,429 tokens per session scan A 36d1711f484a
industry-research AGENTS.md is an instructions file published in the GitHub repository geekjourneyx/industry-research (21 stars, last pushed 2mo ago), licensed MIT. It adds 1,429 tokens to every session, about $0.0071 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.