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 skills add jenningsallen-art/second-brain-os --skill distillgit clone --depth 1 https://github.com/jenningsallen-art/second-brain-osWrote 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/skills/jenningsallen-art/second-brain-os/distill)<a href="https://agentmods.dev/skills/jenningsallen-art/second-brain-os/distill"><img src="https://agentmods.dev/badge/skills/jenningsallen-art/second-brain-os/distill/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/skills/jenningsallen-art/second-brain-os/distill"><img src="https://agentmods.dev/badge/skills/jenningsallen-art/second-brain-os/distill.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 | $0.00103 | $0.01977 |
| Opus 5 | $0.00051 | $0.00988 |
| Sonnet 5 | $0.00021 | $0.00395 |
| Haiku 4.5 | $0.00010 | $0.00198 |
Grade A, and why
distill 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 11d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Distill
Convert the user's thinking into polished written output. The motion is always the same: raw input goes in, argument-in-prose comes out. Structure is the skeleton — invisible in the output, doing the work underneath.
Read Memory.md before drafting. Its Writing Rules and How I Work sections are the
user's own style constraints, and they are hard rules, not suggestions. If the user has
not personalized them yet, fall back to the defaults in Step 4 and say which you used.
The Core Problem This Skill Solves
AI defaults to surfacing the organizing framework as the communication vehicle. "Three pillars of X." "Four categories of Y." "The framework has five components." The framework becomes memorable; the message becomes forgettable.
People think in outlines. Outlines are the right input mode — they organize thinking. This skill translates outlines into argument, not into listicles. The reader should be able to quote the main idea, not name the structure.
The test: after reading the output, can the reader describe it without naming a framework or category? If they say "it's about the three pillars of the data strategy" — the draft failed. If they say "it's about why the data team has to own definitions, not just dashboards" — it worked.
This is the whole reason the skill exists. Everything below serves it.
Output Formats
| Format | When | Structure visible? | Length |
|---|---|---|---|
| Memo | Audience-facing argument: leadership, cross-functional | No | 300-600 words |
| Message | Email or chat to a specific person | No | As short as possible |
| Position | Internal only — working out a theory, stance, or framing | Minimal | Open-ended, preserve uncertainty |
| Brief | Reference or background doc | Yes (headers OK) | As needed |
Step 1: Take the raw input
Accept any state:
- An outline or bullet list
- Output from a
thinking-partnersession - A half-thought: "I want to say something about X"
- A clear brief: "write a memo to the CFO about the vendor renewal"
- An existing draft that needs rework
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.
- 11d ago First seen · 203 lines · 103 tokens per session scan A 81e1bd12d25b
distill is a skill published in the GitHub repository jenningsallen-art/second-brain-os (2 stars, last pushed 1mo ago), licensed MIT. It adds 103 tokens to every session and 1,977 once invoked, about $0.0005 per session on Opus 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 2026-08-31.
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