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 ai-ecoverse/slicc --skill memorygit clone --depth 1 https://github.com/ai-ecoverse/sliccWrote 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/ai-ecoverse/slicc/memory)<a href="https://agentmods.dev/skills/ai-ecoverse/slicc/memory"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/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/ai-ecoverse/slicc/memory"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/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 | $0.00109 | $0.01180 |
| Opus 5.5 | $0.00044 | $0.00472 |
| Sonnet 5.5 | $0.00022 | $0.00236 |
| Haiku 4.5 | $0.00011 | $0.00118 |
Grade A, and why
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 21d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory — inspect and manage durable cone memory
Durable memory is one markdown file per cone — /workspace/CLAUDE.md for the primary cone, /cones/<folder>/CLAUDE.md for extra cones. Agents write these files only through the memory_write tool, which enforces the budget (over budget, a write must shrink the file) and reports the remaining room; other writers are refused. After a chat freezes, a memory-curator scoop rewrites that file from the archived session. A pass reads only its visiblePaths from /etc/MEMORY.md; a path outside them is unknown to it, never absent — the runtime notes such blind reads on the pass's command results and memory_write refuses a line that records one as missing (slicc#3459). A live archive (/sessions/live-*.md) is also mined a slice at a time while the chat is still open (curatedThrough); "New chat" then mines only the remainder. /sessions/index.json is the per-archive ledger of whether that pass succeeded (memoryCuratedAt), failed (memoryFailed), is still owed (memoryPending), or was skipped by the user (memorySkipped).
Usage
memory show [--cone <folder>] # the cone's memory file, verbatim
memory status [--json] [--check] # files, budget, curation tally, health
memory log [--limit N] # per-archive ledger, newest first
memory curate [--archive <file>] [--cone <folder>] # run a curator pass now
memory dream [--cone <folder>] [--all] [--wait] # consolidate memory (dreamer pass)
When to reach for it
- "What do you remember about me / this project?" →
memory show. - A fact you expected to be remembered is missing →
memory logto see whether the session that established it was ever curated;memory status --checkfor systemic failures. - After a failed curation (
memoryFailedin the log) → fix the cause if visible (usually a missing provider or a timeout), thenmemory curate --archive <that-file>. - The memory file has grown duplicated, contradictory, or over budget →
memory dream(add--waitto see the dreamer's report;--allfor every cone with a memory file). The gelatiere's nightly already runsmemory dream --all, so reach for this manually only when it cannot wait. - Extra cones keep separate memory: pass
--cone <folder>toshow,curate, anddream. The folder must exist (cone, or a/cones/<folder>);curatewithout it targets the cone the archive was frozen from.
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.
- 21d ago Changed 9bf18ef17a8c
- 24d ago Changed a14a1e5299fb
- 1mo ago Changed 1c8c0db0f502
- 1mo ago First seen · 49 lines · 109 tokens per session scan A e0355cc34372
memory is a skill published in the GitHub repository ai-ecoverse/slicc (34 stars, last pushed yesterday), licensed Apache-2.0. It adds 109 tokens to every session and 1,180 once invoked, about $0.0004 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 2026-09-12.
Other skills, from other repositories
learnings
Use for repeated-looking troubleshooting, solved-issue recall, adding durable troubleshooting notes, and maintaining the local LEARNINGS archive. Reads LEARNINGS-SUMMARY.md first, follows referenced archive/source files before applying lessons, and verifies against current system evidence.
contextdb-autopilot
Automatic ContextDB session lifecycle — init, session events, checkpoints, and continuity artifacts. Use when you need AIOS context persistence without prompt injection. NOT for general task execution — only for ContextDB session management. TRIGGER: contextdb、session persist、checkpoint save.
memo
AIOS project memory — read/write/search your own memory using the memo capabilities. You (the model) decide what to remember, what to correct, and what was useful; the harness only executes your decision. Use when you want to recall prior work, persist a durable fact, supersede a wrong one, or mark a recalled memory…
aios-offload-recall
Use when recalling prior AIOS tool/browser outputs from offloaded refs; inspect Mermaid canvas first, then read only matching node-level evidence.
memory-search
Runs read-only SQL over the local EvoFlux session database (evoflux.db) for structured analysis that ordinary recall cannot answer, such as aggregating tool failures across sessions, filtering turns by role, agent, or time range, reconstructing a complete execution chain, or checking a remembered claim against what a…
map
Per-site navigation memory for tandem's shared browser. Profiles that describe a site's skeleton (routes), its durable locators, navigation recipes, and gotchas, so you navigate KNOWING instead of re-deriving the DOM each time. Use it when you start operating a site (check whether a profile already exists), when you…