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.
npx agentmods add instructions/jepegit/issue-flow/agents-mdgit clone --depth 1 https://github.com/jepegit/issue-flowWhat 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 | $0.06933 | $0.06933 |
| Opus 5 | $0.03467 | $0.03467 |
| Sonnet 5 | $0.01387 | $0.01387 |
| Haiku 4.5 | $0.00693 | $0.00693 |
Grade A, and why
issue-flow 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 yesterday.
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 — 427 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for AI agents working in the issue-flow repository.
What this project is
issue-flow is a small Python CLI that scaffolds a lightweight, agent-friendly
issue-tracking workflow into other projects. Running issue-flow init writes a
.issueflows/ tracking tree plus editor skills, rules, and command files where
the selected editor still needs them, so AI agents can pick up GitHub issues,
plan work, and land PRs in a consistent way.
This repo is the tool itself — not a project that has been scaffolded by it.
- Package name:
issue-flow(moduleissue_flow) - Entry point:
issue-flow = "issue_flow.cli:main" - Requires Python 3.11+ (development pin: 3.13 in
.python-version) - Source of truth for scaffolded files: Jinja2 templates under
src/issue_flow/templates/
Environment & tooling
This project uses a uv-managed virtual environment (.venv). Use uv
exclusively for dependency management and running code — never pip,
pip-tools, or poetry.
uv sync # install/refresh all deps from the lock file
uv add <package> # add or upgrade a dependency
uv remove <package> # remove a dependency
uv run <script.py> # run a script with the right environment
❌ python run_script.py → ✅ uv run run_script.py
Common commands
uv run pytest # run the test suite
uv run ruff check src/ tests/ # lint
uv version --bump <part> # bump version (used by /iflow-close)
Project layout
src/issue_flow/
cli.py # Typer CLI: init / update / graphify
init.py # scaffolding logic (writes .issueflows/ + .cursor/)
config.py # env-driven config (ISSUEFLOW_* vars, .env)
dependencies.py # external-CLI checks (git, gh)
templating.py # Jinja2 rendering helpers
graphify.py # optional graphify integration
templates/ # Jinja2 templates for all scaffolded output
commands/ # /iflow-* slash commands
skills/ # Agent Skills
rules/ # always-on Cursor rule
tests/ # pytest suite
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.
- yesterday First seen · 427 lines · 6,933 tokens per session scan A 7b2b3ddd8f03
issue-flow AGENTS.md is an instructions file published in the GitHub repository jepegit/issue-flow (4 stars, last pushed 19d ago), licensed MIT. It adds 6,933 tokens to every session, about $0.0347 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 2026-08-31.
Other instructions, from other repositories
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.
buildNext
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).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain 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.