harmonyhub-py AGENTS.md

harmonyhub-py AGENTS.md is an instructions file for Codex, OpenCode from jenreh/harmonyhub-py. It costs 1,352 tokens per session, scanned A, original, MIT.

Project-specific development instructions for the HarmonyHub Python codebase, covering its tools, technologies, and working practices.

In plain words
What is it for?
Use them when planning and implementing changes in the project, especially Python, Reflex, FastAPI, SQLAlchemy, Alembic, and Pydantic work.
Why use it?
They give a coding agent consistent rules for testing, logging, migrations, file size, memory, and keeping changes focused.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

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/jenreh/harmonyhub-py/agents-md
Clone the repo
git clone --depth 1 https://github.com/jenreh/harmonyhub-py

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for harmonyhub-py AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/jenreh/harmonyhub-py/agents-md.svg)](https://agentmods.dev/instructions/jenreh/harmonyhub-py/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/jenreh/harmonyhub-py/agents-md"><img src="https://agentmods.dev/badge/instructions/jenreh/harmonyhub-py/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,352 This file is loaded in full into every session.
When invoked 1,352 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 5.1 $0.01352 $0.01352
Opus 5 $0.00676 $0.00676
Sonnet 5 $0.00270 $0.00270
Haiku 4.5 $0.00135 $0.00135

Measured 6d ago against content hash f2400ba2d04a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

harmonyhub-py 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 6d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

harmonyhub-py


1) Golden Rules

  1. Think → Memory → Tools → Code → Memory. Use code-reasoning; search Memory and claude-context first; minimal diff; write learnings back.
  2. Tests are truth. Failures → fix code first. Change tests only if clearly wrong spec.
  3. Minimal diff. Add tests before code. Keep simple.
  4. Consistency > cleverness. Follow SOPs and stack idioms.
  5. Memory multiplies. Persist decisions, patterns, error signatures, proven fixes.
  6. Files ≤ 1000 lines. Exceed → refactor (see §5).
  7. No extensive docs/summaries/comments unless requested.
  8. No --autogenerate for Alembic migrations; write manually.
  9. No cat to create files; use tools.
  10. Log default: logger.debug. Important events: logger.info. Issues only: logger.warning/error. No print.
  11. Caveman skill applies to all writes here.

Prefer local changes over cross-module refactors.


2) Task Bootstrap Pattern

<!-- plan:start
goal: <one line clear goal>
constraints:
- Python 3.13; Reflex UI; FastAPI; SQLAlchemy 2.0; Alembic; Pydantic; appkit_mantine;
- logging: no f-strings in logger calls
- files ≤ 1000 lines; apply design patterns where appropriate
- minimal diff; add/adjust tests first
definition_of_done:
- tests pass; coverage ≥ 80% (non-Reflex classes & Reflex states); lint/type checks clean; memory updated
steps:
1) Search Memory for "<keywords>"
2) Draft/adjust failing test to capture expected behavior
3) Implement minimal code change
4) Run task test; iterate until green
5) Update Memory: decisions, patterns, error→fix
plan:end -->

3) Tooling Decision Matrix

Situation Primary Secondary Store to Memory
API/pattern uncertainty Context7 Canonical snippet + link; edge cases
Ecosystem bug/issue DuckDuckGo Context7 Minimal repro; versions; workaround
Repeated test failure Memory (search) Context7 Error signature → fix; root cause
New feature scaffold Context7 How‑to snippet; checklist
House style/tooling This file Context7 Checklist results

Read the full file on GitHub · 157 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. 6d ago First seen · 157 lines · 1,352 tokens per session scan A f2400ba2d04a

Subscribe to this mod's changes

harmonyhub-py AGENTS.md is an instructions file published in the GitHub repository jenreh/harmonyhub-py (6 stars, last pushed 17d ago), licensed MIT. It adds 1,352 tokens to every session, about $0.0068 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.

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