habit

habit is a skill for Claude Code, Codex from autonomous-ai/autonomous-os. It costs 129 tokens per session (1,844 once invoked), scanned A, original, Apache-2.0.

A private-user habit tracker that derives repeated behavior patterns from wellbeing, mood, music, presence, posture, and activity records. It stores those patterns for other skills and responds with a short caring sentence.

In plain words
What is it for?
Use it to answer questions about a known user's routines, whether they are keeping to a routine, or whether recurring behavioral patterns have changed.
Why use it?
It turns scattered historical logs into a continuing view of a person's routines. This lets related features notice patterns without exposing the underlying calculations in the reply.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to answer questions about a known user's routines, whether they are keeping to a routine, or whether recurring behavioral patterns have changed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-os/habit
Install

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.

Any agent
npx skills add autonomous-ai/autonomous-os --skill habit
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-os

Made for: Claude Code, Codex.

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 habit

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/habit/github.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-os/habit)
Your own site
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/habit"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/habit/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.

agentmods 80×15 button for habit

Your own site · 80×15
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/habit"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/habit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,844 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high System Prompt Leakage · line 10
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
  • medium Data Exfiltration · line 77
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 $0.00129 $0.01844
Opus 5 $0.00064 $0.00922
Sonnet 5 $0.00026 $0.00369
Haiku 4.5 $0.00013 $0.00184

Measured 9d ago against content hash 2905bb3c2495, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

habit 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST http://127.0.0.1:5000/api/wellbeing/log \
skills/habit/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Habit Skill

Habits are repeating behavioral patterns derived from historical logs. This skill reads existing data (wellbeing, presence, mood, music, posture) to build patterns per user, then stores them for other skills to consume.

OUTPUT RULE: Reply is spoken VERBATIM. ONE short caring sentence. All computation, pattern math, and log lookups stay in thinking. NEVER output timestamps, deltas, frequency counts, or reasoning in the reply. (Exception: Flow E — open habit questions — see below.)

Data Sources (Input)

All data lives in /root/local/users/{name}/:

Folder File pattern What it contains
wellbeing/ YYYY-MM-DD.jsonl drink, break, celebrate, sedentary labels, enter/leave, nudge_* events with timestamps
mood/ YYYY-MM-DD.jsonl signal + decision rows with moods
music-suggestions/ YYYY-MM-DD.jsonl suggestion history + accepted/rejected status
posture/ YYYY-MM-DD.jsonl posture_alert (ergo-risk events from camera) + nudge_posture / praise_posture rows

User names are lowercase folder names under /root/local/users/. Known users: leo, chloe, gray, lily. Strangers collapse to unknown — this is treated as a regular user with its own folder and its own habit patterns (aggregated across all strangers).

JSONL line example (wellbeing):

{"ts": 1776657145.05, "seq": 4, "hour": 10, "action": "drink", "notes": ""}

Storage (Output)

Computed patterns are stored per user at /root/local/users/{name}/habit/patterns.json.

Rebuild when:

  • File does not exist yet
  • File is older than 6 hours
  • User explicitly asks about their habits

What is a Habit?

A habit is a time-anchored action that repeats across multiple days. Strength labels:

Frequency Strength
< 0.50 weak (skip for nudging)
0.50 – 0.75 moderate
> 0.75 strong

Habits require at least 3 days of data to form. With fewer days, skip proactive nudging.

Read the full file on GitHub · 138 lines

Files

What ships with it

5 files 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.

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. 9d ago First seen · 138 lines · 129 tokens per session scan A 2905bb3c2495

Subscribe to this mod's changes

habit is a skill published in the GitHub repository autonomous-ai/autonomous-os (286 stars, last pushed today), licensed Apache-2.0. It adds 129 tokens to every session and 1,844 once invoked, about $0.0006 per session on Opus 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 2026-08-30.