EverOS is a Python library and local-first memory runtime that gives AI agents a portable memory layer across apps, devices, and workflows. It stores conversations, files, and agent activity as readable Markdown while maintaining local indexes for retrieval and reuse. The catalogue add-ons provide commands, skills, hooks, and settings for using EverOS with coding agents.
Borrowing it
Nothing to install: this file belongs to EverMind-AI/EverOS. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/EverMind-AI/EverOS/main/.claude/skills/verify-everos/SKILL.mdgit clone --depth 1 https://github.com/EverMind-AI/EverOSWrote 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/evermind-ai/everos/verify-everos)<a href="https://agentmods.dev/skills/evermind-ai/everos/verify-everos"><img src="https://agentmods.dev/badge/skills/evermind-ai/everos/verify-everos/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/evermind-ai/everos/verify-everos"><img src="https://agentmods.dev/badge/skills/evermind-ai/everos/verify-everos.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 | $0.00068 | $0.01794 |
| Opus 5.5 | $0.00027 | $0.00718 |
| Sonnet 5.5 | $0.00014 | $0.00359 |
| Haiku 4.5 | $0.00007 | $0.00179 |
Grade A, and why
verify-everos scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
`curl -s http://127.0.0.1:$PORT/health` answers 200 within a few seconds. How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/verify-everos - check a change on a real server
Unit and integration tests run the code with stand-ins; this is how to see
the real everos server do it. Grown one task at a time: each task adds the
features it actually walked (see the feature map at the end), nothing more.
1. Start your own instance
Never use ~/.everos or a server someone else started. Give every check its
own root and port.
ROOT=$(mktemp -d)/root; PORT=18611
lsof -nP -iTCP:$PORT -sTCP:LISTEN # must print nothing
uv run everos init --root "$ROOT"
EVEROS_LLM__API_KEY=$OPENROUTER_API_KEY \
EVEROS_EMBEDDING__API_KEY=$DEEPINFRA_API_KEY \
EVEROS_RERANK__API_KEY= \
uv run everos server start --root "$ROOT" --port $PORT > "$ROOT.log" 2>&1 &
echo $! > "$ROOT.pid"
The shipped defaults point the LLM at OpenRouter and the embedding at
DeepInfra, so those two keys are all it needs. Reflection is off by default
(docs/reflection.md); to turn it on, replace the $ROOT/ome.toml that
init scaffolds with [strategies.reflect_episodes]\nenabled = true before
starting, as the acceptance tests do.
2. Is it ready?
curl -s http://127.0.0.1:$PORT/health answers 200 within a few seconds.
Its cascade.pending is the number of markdown changes not yet in the index.
Before reading the index, poll it once a second until it reads 0 on two
consecutive samples (docs/api.md, and wait_converged in
tests/acceptance/memory_delete/observe.py): a single 0 can come between a
markdown write and its projection being queued. A server that exits instead: the last
lines of $ROOT.log (usually a missing key).
3. Drive it
- HTTP:
POST /api/v2/memory/add,/flush,/delete(user_id/agent_id/session_id),/delete_by_ids({"memory_type": "episode", "memory_ids": ["<owner>_<entry_id>"]}),/memory/search,/memory/get. Run Reflection now withPOST /api/v2/ome/trigger {"name": "reflect_episodes", "force": true}. - Claude Code, the way users do it: run everos-mcp against your port and
start Claude Code with only that server, in a tmux socket of your own
(
tmux -L <name>), sending keys and reading the pane:
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.
- yesterday First seen · 111 lines · 68 tokens per session scan A 64b56642eac2
verify-everos is a skill published in the GitHub repository EverMind-AI/EverOS (13,824 stars, last pushed yesterday), licensed Apache-2.0. It adds 68 tokens to every session and 1,794 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-05.
verify-everos compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| verify-everosEverMind-AI/EverOS | Skill | 14k | yesterday | Apache-2.0 | A | 68 | Claude Code |
| dev-browserMemTensor/MemOS | Skill | 12k | 2d ago | Apache-2.0 | A | 84 | Claude Code, Codex |
| computer-historyMemTensor/memmy-agent | Skill | 2.2k | today | MIT | A | 42 | Claude Code, Codex |
| docxMemTensor/memmy-agent | Skill | 2.2k | today | MIT | A | 40 | Claude Code, Codex |
| update-setupMemTensor/memmy-agent | Skill | 2.2k | today | MIT | A | 0 | Claude Code, Codex |
| skill-creatorMemTensor/memmy-agent | Skill | 2.2k | today | MIT | A | 28 | Claude Code, Codex |
| memmy-memoryMemTensor/memmy-agent | Skill | 2.2k | today | MIT | A | 34 | Claude Code, Codex |