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/t-rav/hydraflow/agents-mdgit clone --depth 1 https://github.com/T-rav/hydraflowWhat 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 | $0.05037 | $0.05037 |
| Opus 5 | $0.02518 | $0.02518 |
| Sonnet 5 | $0.01007 | $0.01007 |
| Haiku 4.5 | $0.00504 | $0.00504 |
Grade A, and why
hydraflow 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 2d 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 — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Canonical reference for every agent role in HydraFlow. Each section documents:
- Role — what the agent does and its constraints
- Prompt structure — required sections and ordering
- Output contract — exact markers the system parses
- Key rules — non-negotiable constraints
Source of truth for prompt intent. Prompt text lives in the runner files; this document explains why each prompt is structured the way it is.
Agent Runtimes
HydraFlow is runtime-agnostic. The same prompt contracts work with any
agent CLI that can read a prompt from stdin / a flag and write text to stdout.
The output markers (PLAN_START, VERDICT:, SUMMARY:, etc.) are plain text
and impose no tool-specific requirements.
Supported runtimes
| Runtime | CLI invocation | Config key |
|---|---|---|
| Claude Code | claude -p "<prompt>" |
planner_tool = "claude" |
| OpenAI Codex | codex "<prompt>" |
planner_tool = "codex" |
| Pi.dev | pi "<prompt>" |
planner_tool = "pi" |
Each stage (plan, implement, review, HITL) can use a different runtime:
HYDRAFLOW_PLANNER_TOOL=claude
HYDRAFLOW_IMPLEMENT_TOOL=codex
HYDRAFLOW_REVIEW_TOOL=claude
HYDRAFLOW_HITL_TOOL=pi
What the runtime must support
For any runtime to work with HydraFlow:
- Stdin / flag prompt ingestion — the prompt is passed as a positional
argument or
--promptflag. - Filesystem access — the agent must be able to read files in the working directory (read-only for the planner, read-write for others).
- Shell tool access —
make lint,make quality,gitcommands must be executable from within the agent session (for implementer and reviewer). - Plain-text stdout — output markers are parsed from raw stdout/stderr; no structured JSON response format is required.
Output marker stability
The following markers are parsed by HydraFlow's Python code and must not be renamed without a coordinated update to the corresponding runner:
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.
- 2d ago First seen · 474 lines · 5,037 tokens per session scan A 8a771462115b
hydraflow AGENTS.md is an instructions file published in the GitHub repository T-rav/hydraflow (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 5,037 tokens to every session, about $0.0252 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
skills CLAUDE.md
Instructions for jsmastery-pro/skills, covering project: engineering workflow skills, conventions every skill follows, layout and skills.
lead-dev-os CLAUDE.md
Instructions for CaptainMe-AI/lead-dev-os, covering claude.md, project, terminology, plugin architecture and repository structure.
shanraisshan CLAUDE.md
Claude Code instructions for shanraisshan/shanraisshan, covering claude.md, what this repo is, key files, badge formatting rules and reddit views (badges at >= 50k).
jrag CLAUDE.md
Instructions for HumanBean17/jrag, covering jrag, python environment, tests, docs and shipped artifacts.
sprawling AGENTS.md
Instructions for 2youg1/sprawling, covering agents.md — how work is done in this repository, the loop, read before you write, one change, five steps and the rules a machine holds.
deckforge AGENTS.md
Instructions for tph-kds/deckforge, covering deckforge agent entry point, code intelligence, read order, default routing and non-negotiable implementation rules.