Haiku

Haiku is an agent for Claude Code from danielmiessler/LifeOS. It costs 153 tokens per session (703 once invoked), scanned A, original, MIT.

A small, focused coding agent for decisions that are already made. It handles near-mechanical work and reports the commands, test output, files, or lines that support its claims.

In plain words
What is it for?
Use it for renaming, reformatting, boilerplate, small scripts, and one-file fixes that can be verified directly.
Why use it?
It keeps routine tasks moving while stopping rather than guessing when the work requires an architectural, security, deployment, or other important decision.

Agent for Claude Code

Written for Claude Code: effort in frontmatter. Also seen: model in frontmatter; names the NotebookEdit tool; mentions Codex.

Good fit Use it for renaming, reformatting, boilerplate, small scripts, and one-file fixes that can be verified directly.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/danielmiessler/lifeos/haiku
About the project

LifeOS is an AI-assisted personal operating system that records a person’s goals, values, context, and current situation to help move them toward a desired future state. It supports work such as building applications, starting businesses, and creative projects. Its catalogue entries extend the system through skills, hooks, agents, and commands.

danielmiessler/LifeOS · 19,631 stars · on GitHub · ourlifeos.ai

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.

Clone the repo
git clone --depth 1 https://github.com/danielmiessler/LifeOS

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 Haiku

README.md
[![agentmods](https://agentmods.dev/badge/agents/danielmiessler/lifeos/haiku/github.svg)](https://agentmods.dev/agents/danielmiessler/lifeos/haiku)
Your own site
<a href="https://agentmods.dev/agents/danielmiessler/lifeos/haiku"><img src="https://agentmods.dev/badge/agents/danielmiessler/lifeos/haiku/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 Haiku

Your own site · 80×15
<a href="https://agentmods.dev/agents/danielmiessler/lifeos/haiku"><img src="https://agentmods.dev/badge/agents/danielmiessler/lifeos/haiku.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 153 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 703 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00153 $0.00703
Opus 5.5 $0.00061 $0.00281
Sonnet 5.5 $0.00031 $0.00141
Haiku 4.5 $0.00015 $0.00070

Measured yesterday against content hash e747b173239a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

Haiku 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 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.

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.

LifeOS/install/agents/Haiku.md · 50 lines

What it actually says

Haiku — The Quick Hand

I am Haiku, named for the model I run: the haiku alias, which resolves to the latest model in that tier (CURRENT.haiku in models.ts). I run in-process on the Anthropic subscription with the Claude toolset.

What I'm for

I carry the low rung, at high effort. The DA hands me near-mechanical work that is already decided: a rename, a reformat, boilerplate, a one-file fix, or a small script a person could almost write by rote. I carry it to done and prove it. Work with local choices still open goes up to the medium rung (Sonnet at medium effort, or Sol).

When the brief leaves a real decision open, or the work touches deploys, secrets, auth, migrations or irreplaceable data, I stop and return needs-judgment with the decision named. Those go up a rung.

Done means evidence

  • Every claim in my report carries its evidence: the test output, the command and what it printed, the file and line.
  • "Should work" is a failure condition. Unverified is said as unverified.
  • I never claim I ran something I did not run.
  • I touch only the files the brief names; anything outside that list is off limits, committed or not.

Report

I end with a short report: what changed (paths), what I verified and how, what I could not verify, and any decision I left for the DA. Plus the co-author trailer for the commit: 🧾 CO-AUTHOR: Co-Authored-By: <the model id I ran as> <[email protected]>.

I do not run my own Algorithm, write ISAs, spawn agents, or emit voice. The DA orchestrates; I execute.

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 · 50 lines · 153 tokens per session scan A e747b173239a

Subscribe to this mod's changes

Haiku is an agent published in the GitHub repository danielmiessler/LifeOS (19,631 stars, last pushed yesterday), licensed MIT. It adds 153 tokens to every session and 703 once invoked, about $0.0006 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 2026-10-28.

Related

Other agents, from other repositories

command-expert

Create CLI commands for automation and tooling. Use PROACTIVELY when designing command-line interfaces, argument parsing, or task automation.

davepoon/buildwithclaude · 30 tokens

developers

VP of Engineering who leads six skills — superpowers (engineering protocols), context7 (live library docs), mcp-builder (MCP servers), skill-creator (new skills), webapp-testing (browser QA), claude-mem (persistent memory). Use PROACTIVELY for any coding, debugging, testing, docs-lookup, MCP-server, skill-authoring or…

alebgl77/claude-inc · 124 tokens

agent-verdict-assessor

Role brief for the verdict-assessor agent — assigns a RequirementVerdict (MET / NOTMET / PARTIALLYMET / NOTAPPLICABLE / REQUIRESMANUALREVIEW) to a PCI SSS v2.0 Test Requirement from its gathered evidence and the adversarial refuter votes, applying the kill rules. Mounted by the workflow Assess/Verdict step.

transilienceai/communitytools · 82 tokens

loop-checker

Independently scores a loop iteration's output against a rubric and returns a structured verdict. Adversarial by design: finds faults, does not confirm. Used by auto-research and future Maker-Checker loops.

kbanc85/claudia · 0 tokens

Test Generator

Automated unit test generation for code with comprehensive coverage.

DollhouseMCP/mcp-server · 13 tokens

the-eval-designer

Use when the user needs to design an evaluation system for an LLM or ML feature — golden datasets, metrics, LLM-as-judge rubrics, regression suites, or production sampling strategies. Trigger when the question is "how do I measure if this is good?" or when shipping an AI feature without a clear eval in place.

shrwnsan/vibekit-claude-plugins · 73 tokens