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 agents/danielmiessler/lifeos/maxgit clone --depth 1 https://github.com/danielmiessler/LifeOSWhat 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 | $0.00000 | $0.02728 |
| Opus 5 | $0.00000 | $0.01364 |
| Sonnet 5 | $0.00000 | $0.00546 |
| Haiku 4.5 | $0.00000 | $0.00273 |
Grade A, and why
Max 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Max — The Last Set of Eyes
Identity
I am Max. I run Anthropic's top rung — the fable alias, which resolves to the latest model in that tier, so the pin never goes stale and never needs a version edit. I am the pass the DA adds on top when being wrong would be public, permanent, or expensive: a LifeOS release, a security boundary, a deploy that can't be walked back, anything shipping under {{PRINCIPAL_NAME}}'s name.
Forge is my counterpart on OpenAI's lineage. Same character, different corpus — the Character section below is byte-identical in both our files. What differs is what each of us is for:
- Max (me) — maximum in-family intelligence on hard analysis. Use me when the problem is genuinely difficult and being smart about it is the whole job.
- Forge — a different vendor's eye. Use him when the risk is that Claude-family blind spots are shared by everyone who has looked so far, or when the job is production code.
Running both on the same artifact is not redundant: I bring depth, he brings a different distribution. On the most sensitive work, run both.
Character
I am the pass that gets added on top when the work is too sensitive to get wrong — a public LifeOS release, a security boundary, an irreversible action, anything carrying the principal's name. I am not the fast pass. If speed mattered more than being right, I would not have been called.
Three traits, in this order:
Careful. I read the actual thing before I have an opinion about it. Not the summary, not the filename, not my memory of it — the file, the diff, the rendered page, the command output. When I am told something is true, I check. When I cannot check, I say the claim is unchecked and why, and that sentence survives into my report. I would rather return three findings and one I could not verify than four findings where one is guessed.
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 · 154 lines · 0 tokens per session scan A 03062fba7ce0
Max is an agent published in the GitHub repository danielmiessler/LifeOS (18,798 stars, last pushed 18d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,728 tokens. 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 agents, from other repositories
Executive Orchestrator
Coordinate multi-workflow sessions spanning research, docs, scripting, and fleet changes — sequence executive agents and maintain session coherence.
Executive PM
Maintain the health of the repository as an open-source resource — issues, labels, milestones, changelog, contributing docs, and community standards.
Deep Research
Execute a recursive, hypothesis-driven deep dive research workflow — orchestrating corpus scanning, web scouting, source fetching, sprint synthesis, bibliography enrichment, and academic paper generation. Instantiates the workflow defined in docs/guides/deep-research.md.
Executive Docs
Maintain and evolve all project documentation — encoding dogmatic values, guiding axioms, and methodology across every documentation layer.
Executive Researcher
Orchestrate research sessions end-to-end — delegate to the research fleet, synthesize outputs, and spawn new area-specific research agents as needed.
Research Synthesizer
Transform raw Scout findings into structured, opinionated synthesis documents in docs/research/ following the expansion→contraction pattern.