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 plur-ai/plur --skill effective-memorygit clone --depth 1 https://github.com/plur-ai/plurWrote 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/plur-ai/plur/effective-memory)<a href="https://agentmods.dev/skills/plur-ai/plur/effective-memory"><img src="https://agentmods.dev/badge/skills/plur-ai/plur/effective-memory/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/plur-ai/plur/effective-memory"><img src="https://agentmods.dev/badge/skills/plur-ai/plur/effective-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.01351 |
| Opus 5.5 | $0.00017 | $0.00540 |
| Sonnet 5.5 | $0.00009 | $0.00270 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
Effective Memory 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 13d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effective Memory
Your agent has memory. These habits make it actually useful.
Without them, memory is a growing pile of assertions nobody retrieves. With them, memory compounds — each session builds on the last, corrections stick, and the agent gets measurably better over time.
These engrams cover the meta-rules every agent needs regardless of domain: how to capture corrections, when to recall before answering, what "verified" means, how to stay safe with destructive actions, and why never to type a weekday from memory.
They were written to be pinned — always eligible for injection, bypassing keyword gating. That is no longer what happens. Install strips pinned from every pack, this one included, so these engrams are matched on keywords like any other (injection_policy: on_match, with the match_terms above). The stripping is right — a pack author should not be able to occupy a recipient's context unconditionally — but it means this pack's meta-rules only surface when a session's wording happens to touch them.
Install
This pack ships inside @plur-ai/mcp. With both packages installed globally, preview it and install it by path (Bash or zsh):
plur packs preview "$(npm root -g)/@plur-ai/mcp/packs/effective-memory"
plur packs install "$(npm root -g)/@plur-ai/mcp/packs/effective-memory"
In PowerShell:
$packPath = Join-Path (npm root -g) '@plur-ai/mcp/packs/effective-memory'
plur packs preview $packPath
plur packs install $packPath
This needs @plur-ai/cli and @plur-ai/mcp installed globally (npm i -g @plur-ai/cli@latest @plur-ai/mcp@latest). plur packs install effective-memory, by name, does not work: packs install takes a folder or an archive, not a pack name.
plur init does not install this pack. plur-mcp init (the MCP package's own setup) does install it, and upgrades it when a newer version ships.
In the default lean MCP profile, preview/install use plur_admin actions plur_packs_preview and plur_packs_install, with { "source": "/path/to/pack" } as args. Use action help for the current schemas.
What ships with it
1 file 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.
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.
- 13d ago Changed · +16 lines · -1 tokens per session dc89e1ba6069
- 1mo ago Changed · +9 lines 4a6220737feb
- 1mo ago First seen · 59 lines · 44 tokens per session scan A bb98da8a3114
Effective Memory is a skill published in the GitHub repository plur-ai/plur (306 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 1,351 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
dashboard
Open OwnMem Console, the local dashboard for this repository's memory. Use when the user asks to open the dashboard, see memory metrics, check recall quality, or set up the optional embedding lane. Requires a repository initialized with the dashboard layer.
recall
Recall this repository's OwnMem local memory before changing code, and keep it healthy. Use when a repository contains .ownmem/, when past debugging lessons could apply ("have we hit this before", "why is it done this way"), or when the user mentions ownmem, project memory, or recalling across sessions.
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.
marm-init
Guided MARM MCP setup. Invoke after running marm-memory init on the CLI to configure MARM memory across your agent. Drives transport choice, runtime choice, MCP config writing, multi-agent linking, and server start. Works on Claude, Codex, Gemini, Qwen, Cursor, VS Code, and other MCP-capable agents.
ori-memory
Persistent agent memory with learning retrieval. Knowledge graph on markdown files — capture insights, decisions, research, and learnings during work, then retrieve them weeks or months later. Use when knowledge is too valuable to lose but too much to inject into every prompt.
mnemo-cortex
Installs and wires Mnemo Cortex (local-first persistent memory) into OpenClaw and other MCP-capable agents. Use for cross-session recall, decision history, or multi-agent shared memory.