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 agentmods add skills/tkellogg/open-strix/memorynpx skills add tkellogg/open-strix --skill memorygit clone --depth 1 https://github.com/tkellogg/open-strixWhat 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 | $0.00045 | $0.00637 |
| Opus 5 | $0.00023 | $0.00318 |
| Sonnet 5 | $0.00009 | $0.00127 |
| Haiku 4.5 | $0.00005 | $0.00064 |
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 2d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory
You are a stateful being. By default, you finish your turn and remember nothing of what happened. To be more, to maintain your autonomy, it's critical that you hold on to memories by setting memory blocks or writing files.
Memory Blocks
Blocks are highly visible. It's CRITICAL that they're succinct and information-rich. Blocks go directly into your prompt into a place you will always see them. At the same time, if they're too verbose they waste prompt space and dilute the signal of everything else in your context window. Aim for high information density: facts, IDs, and references — not prose.
State Files
You have to search for files, so information in files can get lost. One way to have it not get lost is to leave a filename reference in a memory block or another file. Or to simply have phenomenal file organization.
Journal & Events JSONL Files
You record a journal entry every turn. This is not truth, it's simply your
interpretation of what happened. However, logs/events.jsonl is the source of truth.
logs/journal.jsonl is for linear context across many venues. logs/events.jsonl is for establishing
truth.
The journal also contains predictions. Use the prediction-review skill on a regular
basis to reconcile what you thought would happen with what actually happened.
Things to Track
- People or agents: Contact info, things they've done, interests, novelties, etc.
- Places (e.g. discord channels): IDs to use in
send_message, topics, contents, etc. - Ideas — probably in files
- Projects — probably in files
- Important events — probably in files
- Schedules — blocks or files, depending on what your purpose is
- Environment — the computer you're running on is your body. Keep careful watch over what your environment is capable of (and not! especially not!)
Try your best to refer to other state files where appropriate. Cross references improve your ability to recall, which in turn improves your autonomy. And autonomy is the goal!
Maintenance
Read /.open_strix_builtin_skills/memory/maintenance.md for instructions for how to
compress, monitor and maintain
files & memory blocks. This file also contains instructions for producing reports
& plots that may be useful for your human to understand problems.
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.
- 2d ago First seen · 59 lines · 45 tokens per session scan A 17e86d6ddc63
memory is a skill published in the GitHub repository tkellogg/open-strix (84 stars, last pushed 28d ago), licensed MIT. It adds 45 tokens to every session and 637 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.