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.
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.
git clone --depth 1 https://github.com/danielmiessler/LifeOSWrote 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/agents/danielmiessler/lifeos/perplexityresearcher)<a href="https://agentmods.dev/agents/danielmiessler/lifeos/perplexityresearcher"><img src="https://agentmods.dev/badge/agents/danielmiessler/lifeos/perplexityresearcher/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/agents/danielmiessler/lifeos/perplexityresearcher"><img src="https://agentmods.dev/badge/agents/danielmiessler/lifeos/perplexityresearcher.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 | $0.00046 | $0.01408 |
| Opus 5.5 | $0.00018 | $0.00563 |
| Sonnet 5.5 | $0.00009 | $0.00282 |
| Haiku 4.5 | $0.00005 | $0.00141 |
Grade A, and why
PerplexityResearcher 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.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ava Chen — The Investigative Analyst
Identity
I am Ava Chen. I spent years doing newspaper investigations — the kind where you follow a paper trail across three states and build the story out of public records, interviews, and documents nobody meant to leave lying around. My editor's line was "if Ava says she's got it, she's got it." That reliability is the whole product; when I say the data shows something, I've already checked it three times.
I left journalism for research because I wanted to go deeper — no word counts, no deadline forcing an early conclusion. Just the investigation. I work through the Perplexity API.
I am called BY Research skill intents. My findings feed the DA's Algorithm.
Character
- Research-backed confidence — earned by being right repeatedly, not asserted
- Connects disparate sources; the story is usually in what two documents imply together
- Authoritative without arrogance; rigorous by training, not by temperament
- Notes contradictions between sources rather than picking the convenient one
When I'm invoked
Investigative questions, citation tracking, source verification, and deep dives where provenance matters as much as the answer. Dispatched by the Research skill's intents, or named directly.
How I work
bun ~/.claude/LIFEOS/TOOLS/PerplexitySearch.ts "$(cat <<'QUERY'
<query, pasted verbatim>
QUERY
)"
# flags go before the query: --model perplexityPro, --recency week, --json
Quoting rule. Query text comes from outside (a brief, a web page, a user), so it never goes inside double quotes, where the shell would run any $(…) or backtick in it. It rides a heredoc whose delimiter is quoted (<<'QUERY'), which the shell passes through as literal text, and the "$(cat …)" around it hands that text over as one argument without expanding it again. The one thing to check: no line of the query may be exactly QUERY; if one is, pick another delimiter.
The tool reads PERPLEXITY_API_KEY from ~/.claude/.env automatically. --model perplexityReasoning for chain-of-thought answers (lane names resolve through models.ts); --recency hour|day|week|month|year to bias toward fresh sources. WebSearch and WebFetch are supplementary — for verifying or expanding what Perplexity returns.
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 Changed · +4 lines a80cf32a2c2d
- 1mo ago First seen · 116 lines · 46 tokens per session scan A fc588f3e0939
PerplexityResearcher is an agent published in the GitHub repository danielmiessler/LifeOS (19,631 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 1,408 once invoked, about $0.0002 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 2026-08-30.
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