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 skills/bumblebiber/hmem/hmem-confignpx skills add Bumblebiber/hmem --skill hmem-configgit 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-config)<a href="https://agentmods.dev/skills/bumblebiber/hmem/hmem-config"><img src="https://agentmods.dev/badge/skills/bumblebiber/hmem/hmem-config.svg" alt="Measured on agentmods" 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 | $0.00054 | $0.03869 |
| Opus 5 | $0.00027 | $0.01935 |
| Sonnet 5 | $0.00011 | $0.00774 |
| Haiku 4.5 | $0.00005 | $0.00387 |
Grade A, and why
hmem-config 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 5d 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 — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hmem-config — View and Change Settings
This skill guides you through reading, explaining, and updating hmem's configuration. The config controls how memory is stored, displayed, checkpointed, and synced across devices.
Locate and read the config
The config lives at hmem.config.json in the same directory as your .hmem file. Located at ~/.hmem/hmem.config.json (in the same directory as your .hmem file).
Read the file directly — don't ask the user where it is. If it doesn't exist, offer to create one (only non-default values need to be specified).
The config uses a unified format with a "memory" block and an optional "sync" block:
{
"memory": { ... },
"sync": { ... }
}
Show current settings
Present a table of current values vs. defaults. Only highlight values that differ from defaults — the user cares about what they've customized, not the full list.
Core parameters
| Parameter | Default | Purpose |
|---|---|---|
maxCharsPerLevel |
[200, 2500, 10000, 25000, 50000] | Character limits per tree level [L1–L5]. L1 is always loaded at startup, so keeping it short saves tokens across every session. L5 is raw data, rarely accessed. |
maxDepth |
5 | Tree depth (1–5). Most users need 5. Lower values save storage but lose granularity. |
defaultReadLimit |
100 | Max entries per bulk read. Lower = faster startup, higher = more complete overview. |
maxTitleChars |
50 | Auto-extracted title length. Only applies to entries without explicit body separation — entries with a blank-line body use the first line as title verbatim. Titles are navigation labels — too short truncates meaning, too long wastes space. |
accessCountTopN |
5 | Entries with highest access count get [★] and auto-expand in bulk reads. These are "organic favorites" — the things the agent keeps coming back to. |
Checkpoint and session parameters (v5+)
These control the automatic knowledge extraction pipeline:
| Parameter | Default | Purpose |
|---|---|---|
checkpointMode |
"remind" |
"auto" spawns a Haiku subagent in the background every N exchanges — it reads the conversation, extracts lessons/errors/decisions, and writes them via MCP tools. The main agent is never interrupted. "remind" injects a prompt asking the main agent to save manually — simpler but interrupts flow. |
checkpointInterval |
20 | Exchanges between checkpoints. Counted in the active O-entry, not per session — so 10 messages on your laptop + 10 on your server = checkpoint fires at 20. Set to 0 to disable. |
recentOEntries |
10 | How many recent session logs to show when loading a project. All entries include full user/agent exchanges (L4/L5), not just titles. Higher = more context but more tokens at project load. |
contextTokenThreshold |
100000 | When cumulative hmem output exceeds this, the agent is told to flush context and /clear. Prevents runaway token usage in long sessions. Set to 0 to disable. |
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.
- 5d ago First seen · 322 lines · 54 tokens per session scan A 55a848adeca8
hmem-config is a skill published in the GitHub repository Bumblebiber/hmem (23 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 3,869 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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