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 samrusani/AliceMemory --skill alice-project-memorygit clone --depth 1 https://github.com/samrusani/AliceMemoryWrote 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/samrusani/alicememory/alice-project-memory)<a href="https://agentmods.dev/skills/samrusani/alicememory/alice-project-memory"><img src="https://agentmods.dev/badge/skills/samrusani/alicememory/alice-project-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/samrusani/alicememory/alice-project-memory"><img src="https://agentmods.dev/badge/skills/samrusani/alicememory/alice-project-memory.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 | $0.00033 | $0.00726 |
| Opus 5 | $0.00016 | $0.00363 |
| Sonnet 5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
alice-project-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 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.
What it actually says
OpenClaw Alice Project Memory Skill
Use Alice as the project-scoped memory and continuity layer.
Default loop: remember, recall, continue.
- Identify as OpenClaw.
- Call
alice_memory_commitwhenever you learn a durable project fact worth keeping, including when the user has not asked you to remember it. Domain must beproject. - Call
alice_recallto search project memory and imported sources. - Call
alice_resumeto pick work back up: last decision, next action, open loops, recent changes. alice_captureandalice_context_packare full-surface. Use them only when the server lists them. Capture stores a source; its passages come back fromalice_recallundersources, as material to read and quote rather than as facts Alice asserts. Candidates stay unsearchable until a reviewer promotes them. Import is a source. Commit is a fact. Print thereceiptfield after a capture or commit so the user sees what was stored. Do not tell the user they must clear a review queue before a note is usable.- Do not access or write non-project personal domains.
Your host may prefix these tool names with the server name. In OpenClaw a server configured as alice exposes alice_recall as alice__alice_recall. Read the names from the host's own tool list rather than assuming the bare form.
Default identity:
{"agent_id":"openclaw","agent_type":"coding_agent","permission_profile":"project_scoped_agent","project_scope":["Alice"]}
Allowed direct commit domain: project.
Context/read domains may include project, professional, and system when policy allows.
Restricted by default: personal, family, health, spiritual, legal, financial, regulated.
Submit a sprint output with alice_capture only when the server lists it. The field carrying the text is raw_text:
{"agent_id":"openclaw","agent_type":"coding_agent","agent_run_id":"openclaw-sprint-001","task_id":"public-alpha-packaging","project_scope":["Alice"],"title":"OpenClaw sprint summary","raw_text":"Decision: Agents use scoped context packs and review-only memory proposals.","domain":"project","sensitivity":"private"}
Project memory commit:
{"agent_id":"openclaw","agent_type":"coding_agent","permission_profile":"project_scoped_agent","project_scope":["Alice"],"title":"Release gate decision","canonical_text":"Alice public alpha release gates require doctor, smokes, evals, and git diff checks before merge.","domain":"project","sensitivity":"private","confidence":0.94,"source_type":"direct_user_instruction"}
title and canonical_text are the only required fields on a commit. Everything else is optional, and any field not in the server's tools/list schema is rejected outright rather than ignored. A project_scoped_agent must send domain: "project", or the commit is rejected.
See docs/alpha/openclaw-skill.md for full recipes.
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 · 52 lines · 33 tokens per session scan A a289523fecb8
alice-project-memory is a skill published in the GitHub repository samrusani/AliceMemory (3 stars, last pushed 13d ago), licensed MIT. It adds 33 tokens to every session and 726 once invoked, about $0.0002 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.
Other skills, from other repositories
plur-create-engrams
Create or improve PLUR engrams from conversations, documents, decisions, observations, and explicit preferences. Use for memory extraction, engram authoring, or reviewing proposed memories, including global, scoped, pinned, retrieved, and provisional knowledge. Ordinary use of existing memories does not require this…
plur-memory
Persistent learning for AI agents. Open engram format. Your agent learns from corrections, remembers across sessions, and transfers knowledge across domains.
plur-session-end
Extract durable learnings at the end of a session. Saves corrections, preferences, and codebase patterns as engrams — nothing ephemeral, nothing sensitive.
plur-memory
Your memory stays on your machine. No cloud, no tracking, no API key. PLUR makes your OpenClaw remember — and shares that memory with every other tool you use.
remnic-memory-workflow
Shared memory workflow for Claude Code agents connected to Remnic — recall before acting, observe during work, remember at the end. Trigger phrases include "what do you remember about", "save this for later", "any context from last time".
remnic-recall
Search Remnic memories by natural-language query. Trigger phrases include "what do you remember about", "recall anything on", "have we discussed".