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-continuity-recallgit 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-continuity-recall)<a href="https://agentmods.dev/skills/samrusani/alicememory/alice-continuity-recall"><img src="https://agentmods.dev/badge/skills/samrusani/alicememory/alice-continuity-recall/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-continuity-recall"><img src="https://agentmods.dev/badge/skills/samrusani/alicememory/alice-continuity-recall.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 | $0.00034 | $0.00385 |
| Opus 5 | $0.00017 | $0.00192 |
| Sonnet 5 | $0.00007 | $0.00077 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
alice-continuity-recall 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 11d 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
Alice Continuity Recall
Goal
Produce recall answers from Alice continuity records instead of free-form memory.
Trigger Cues
Use this skill when the user asks:
- what was decided
- what happened in a thread/project/person scope
- what should be remembered from prior work
Required MCP Tools
mcp_<alice_server>_alice_recall- Optional:
mcp_<alice_server>_alice_recent_decisions
<alice_server> is usually alice_core.
Workflow
- Prefer
alice_recallover inference-only answers. - Use hard scope filters when available (
thread_id,task_id,project,person,since,until); Alice applies them before ranked result limits. - Keep
limitbounded (normally3to10). - Return summary plus provenance-backed evidence IDs.
Tool Call Templates
mcp_alice_core_alice_recall({"query":"<topic>","thread_id":"<uuid>","limit":5})
mcp_alice_core_alice_recent_decisions({"thread_id":"<uuid>","limit":5})
Output Contract
Always include:
- direct answer
- top evidence items (
id,title,object_type) - provenance notes from the returned item fields
- uncertainty note if evidence is weak or absent
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.
- 11d ago First seen · 57 lines · 34 tokens per session scan A 2909f3d97c7e
alice-continuity-recall is a skill published in the GitHub repository samrusani/AliceMemory (3 stars, last pushed 14d ago), licensed MIT. It adds 34 tokens to every session and 385 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".