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 xdragonjia/leafmem --skill leafmem-maintenancegit clone --depth 1 https://github.com/xdragonjia/leafmemWrote 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/xdragonjia/leafmem/leafmem-maintenance)<a href="https://agentmods.dev/skills/xdragonjia/leafmem/leafmem-maintenance"><img src="https://agentmods.dev/badge/skills/xdragonjia/leafmem/leafmem-maintenance/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/xdragonjia/leafmem/leafmem-maintenance"><img src="https://agentmods.dev/badge/skills/xdragonjia/leafmem/leafmem-maintenance.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 | $0.00176 | $0.08074 |
| Opus 5.5 | $0.00070 | $0.03230 |
| Sonnet 5.5 | $0.00035 | $0.01615 |
| Haiku 4.5 | $0.00018 | $0.00807 |
Grade A, and why
leafmem-maintenance 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 7d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- CHANGELOG.md 20 KB
- references/cli-write-channel.md 5.1 KB
- references/examples.md 1.0 KB
- references/mcp-channels.md 4.3 KB
- references/scripts-usage.md 5.1 KB
- references/step5b-long-entry-split.md 4.8 KB
- scripts/archive_dump.py 2.0 KB runs code
- scripts/leafmem_mcp_call.py 1.4 KB runs code
- scripts/stale_task_sweep.py 3.9 KB runs code
- scripts/weekly_scan.py 9.7 KB runs code
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.
- 7d ago Changed · -1 lines 96ed7887d8a7
- 10d ago Changed · +5 lines scan B → A 99c8db816fec
- 16d ago Changed · +17 lines · +24 tokens per session 2d808cf7af1d
- 24d ago Changed · -27 lines e4d6793fe0fe
- 27d ago Changed · +11 lines b32ea7c634e3
- 1mo ago Changed · +14 lines scan A → B f7ad523dcdb7
- 1mo ago Changed · +8 lines 6afa4079665c
- 1mo ago Changed · +5 lines 8d2245515edc
- 1mo ago Changed · +2 lines 47ce0dd70797
- 1mo ago First seen · 253 lines · 152 tokens per session scan A b6ccdad7d947
leafmem-maintenance is a skill published in the GitHub repository xdragonjia/leafmem (0 stars, last pushed 3d ago), with no licence file. It adds 176 tokens to every session and 8,074 once invoked, about $0.0007 per session on Opus 5.5. 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 skills, from other repositories
weekly-digests
Generate a serial week-by-week narrative digest of a project's full claude-mem timeline. Splits the timeline into per-ISO-week files, then runs one consecutive subagent per week — each receiving the prior week's carry-forward block — to produce one chapter per ISO week of data. Use when asked for "weekly digests"…
cloud-sync
Set up or check claude-mem cloud sync with cmem.ai Pro. Use when the user says "set up cloud sync", "sync my memories", "cmem pro", "cloud backup", "sync status", or wants their memory database backed up or synced to their cmem.ai account.
screenpipe
Search screen and audio history recorded by Screenpipe and optionally save selected context into claude-mem. Use when the user asks to recall desktop activity, a meeting, or something seen in another app through Screenpipe.
memory-retain
Save what was learned to Hindsight long-term memory. Use when a task finishes, when the user states a fact, decision or preference, and when you discover something a later run or another Bot would need.
hivemind-memory
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.