EverOS: Skill for Claude Code

.claude/skills/verify-everos/SKILL.md

verify-everos is a skill for Claude Code from EverMind-AI/EverOS. It costs 68 tokens per session (1,794 once invoked), scanned A, original, Apache-2.0.

A verification workflow for checking an EverOS change on a real, isolated server. It sends requests over HTTP or through Claude Code, then checks the result in the storage or metrics layer that owns it.

In plain words
What is it for?
Use it to start a temporary EverOS instance, check its health, exercise a memory feature, inspect Markdown, SQLite, LanceDB, or metrics results, and shut the instance down.
Why use it?
Unit and integration tests often use substitutes instead of a running server. This catches problems that only appear when the full EverOS system runs end to end.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions Claude Code.

This is EverMind-AI/EverOS's own configuration. It tells Claude Code how to work on EverOS itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything EverOS configures →

About the project

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.

EverMind-AI/EverOS · 13,824 stars · on GitHub · evermind.ai

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/EverMind-AI/EverOS/main/.claude/skills/verify-everos/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/EverMind-AI/EverOS

Made for: Claude Code.

Wrote 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.

agentmods badge for verify-everos

README.md
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Your own site
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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.

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Your own site · 80×15
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Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,794 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash 64b56642eac2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.
.claude/skills/verify-everos/SKILL.md · 111 lines

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 with POST /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:

Read the full file on GitHub · 111 lines

Changes

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.

  1. yesterday First seen · 111 lines · 68 tokens per session scan A 64b56642eac2

Subscribe to this mod's changes

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.

Related

verify-everos compared with skills from other repositories

verify-everos next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
verify-everosEverMind-AI/EverOSSkill14kyesterdayApache-2.0A68Claude Code
dev-browserMemTensor/MemOSSkill12k2d agoApache-2.0A84Claude Code, Codex
computer-historyMemTensor/memmy-agentSkill2.2ktodayMITA42Claude Code, Codex
docxMemTensor/memmy-agentSkill2.2ktodayMITA40Claude Code, Codex
update-setupMemTensor/memmy-agentSkill2.2ktodayMITA0Claude Code, Codex
skill-creatorMemTensor/memmy-agentSkill2.2ktodayMITA28Claude Code, Codex
memmy-memoryMemTensor/memmy-agentSkill2.2ktodayMITA34Claude Code, Codex