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 skills add Bumblebiber/hmem --skill hmem-new-projectgit clone --depth 1 https://github.com/Bumblebiber/hmemWrote 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/skills/bumblebiber/hmem/hmem-new-project)<a href="https://agentmods.dev/skills/bumblebiber/hmem/hmem-new-project"><img src="https://agentmods.dev/badge/skills/bumblebiber/hmem/hmem-new-project/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/skills/bumblebiber/hmem/hmem-new-project"><img src="https://agentmods.dev/badge/skills/bumblebiber/hmem/hmem-new-project.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 | $0.00065 | $0.00917 |
| Opus 5 | $0.00032 | $0.00458 |
| Sonnet 5 | $0.00013 | $0.00183 |
| Haiku 4.5 | $0.00006 | $0.00092 |
Grade A, and why
hmem-new-project 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/hmem-new-project — New Project Entry
Uses the create_project tool to set up a complete project with one call.
Step 1: Does a codebase exist?
Ask:
"Gibt es bereits eine Codebase? Wenn ja, in welchem Verzeichnis?"
If yes: Scan the directory (README, package.json, CLAUDE.md, etc.) to extract name, tech stack, description, entry points, key modules. Use findings to fill the create_project parameters and later append Codebase details.
If no: All info comes from the user's answers.
Step 2: Quick questions (one at a time)
Ask these in order. Skip what the codebase scan already answered.
- Name — "Wie soll das Projekt heißen?"
- Stack — "Welche Technologien?"
- One-liner — "Beschreib das Projekt in einem Satz"
- Goal — "Was ist das Hauptziel?"
- Who — "Wer nutzt es?"
- Repo — "Repo-Pfad oder URL?"
- Deployment — "Wie wird es deployed?"
Stop early if the user says "reicht" or "das war's".
Step 3: Create the project
create_project({
name: "...",
tech: "...",
description: "...",
goal: "...",
repo: "...",
audience: "...",
deployment: "...",
tags: ["#lang", "#framework"]
})
This creates:
- P00XX with sections from the configured schema (or 9 R0009 defaults if no schema)
- O00XX matching O-entry for session logging (if
createLinkedO: truein schema, or always when no schema)
Step 4: Fill in details
If a codebase was scanned, append the findings. The Codebase node (.2) follows a strict schema:
Codebase node structure
- L3 — Pipeline (first child): Data flow overview —
entry → moduleA → moduleB → storage - L3 — Modules: One node per source file. Title = filename, body = purpose +
src/file.ts - L4 — Functions: Under each module, one node per exported function/class. Title = full TypeScript signature, body = one-line description +
src/file.ts
append_memory(id="P00XX.2", title="Pipeline", body="src/cli.ts → moduleA.ts → DB")
append_memory(id="P00XX.2", title="moduleA.ts", body="Core logic handler. src/moduleA.ts")
append_memory(id="P00XX.2.N", title="doThing(x: string): Promise<boolean>", body="Does the thing. src/moduleA.ts")
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 · 93 lines · 65 tokens per session scan A 7a030f1d1312
hmem-new-project is a skill published in the GitHub repository Bumblebiber/hmem (23 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 917 once invoked, about $0.0003 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.
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