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Get Started Free →The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the `brain` CLI.
.claude/skills/mindmuxai-brain-ingest/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 45% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 135% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 124% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -79% | 0% |
This skill is about "turning scattered input into structured brain knowledge". The input can be a conclusion from a conversation, an external document, a piece of research, or the decisions behind a set of code changes. The goal is to land that knowledge in the right place, the right category, and the right structure — and to write it through the brain CLI so it is correct by construction.
Reach for this process not only when explicitly asked to "ingest" something. The brain is the project's persistent memory (see BRAIN.md), so trigger it proactively whenever knowledge crystallizes — a decision settled in discussion, a requirement or constraint agreed, an insight that will still matter in six months. Capture it as it surfaces rather than waiting to be told.
Every read and write below is a brain CLI subcommand (list-pages / read-page / read-root to read; create-page / update-truth / … to write). The command details and the category taxonomy live in the brain-page skill — read it before creating or modifying any page.
> NEVER hand-edit any file under the brain directory. All reads and writes MUST go through the brain CLI. Manual edits are unsupported and illegitimate. There is no validator and nothing at the file layer can catch a bad manual edit; correctness is guaranteed only by going through the CLI, so a hand edit silently breaks the brain's invariants.
Split the input into individual atomic knowledge points. A knowledge point = one judgment / fact / decision that stands on its own. Ignore purely procedural chatter.
BRAIN.md)brain update-root <slug> (background / architecture / flow / mindmap / stack / roadmap).brain list-pages (and brain read-page <id> on likely hits) to look for an existing page on the same topic.brain update-truth --id <id> (rewrites compiled_truth and appends a timeline entry atomically), or brain append-timeline for a new piece of evidence that doesn't change the conclusion.brain create-page, then fill in the real understanding with brain update-truth.brain CLI — see brain-page for exact commands. Never hand-edit frontmatter or timelines.update-root; they have no timeline.[[page-id]].The write commands reindex for you, and correctness is guaranteed by construction — there is no validator to run. To optionally confirm that every [[page-id]] resolves:
node <brain-page-bundle>/bin/brain.mjs lint-linksThe CLI makes "compiled_truth changed but the timeline entry was forgotten" structurally impossible; the only way to break it is a hand edit, which is why you must never make one.
update-truth guarantees this, keeping the chain of evidence unbroken.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,909 | 17,342 | +75% | 1 | 1 | 0% | 255 | 1,305 | +412% | 0 | 0 | — |
case-02 | fail→fail | 11,366 | 16,177 | +42% | 1 | 1 | 0% | 1,065 | 1,322 | +24% | 0 | 0 | — |
case-03 | fail→fail | 9,352 | 11,229 | +20% | 1 | 1 | 0% | 751 | 1,306 | +74% | 0 | 0 | — |
case-09 | fail→pass | 7,731 | 10,880 | +41% | 1 | 1 | 0% | 1,342 | 1,943 | +45% | 0 | 0 | — |
case-10 | pass→pass | 16,976 | 13,159 | -22% | 1 | 1 | 0% | 2,154 | 2,427 | +13% | 0 | 0 | — |
case-11 | fail→pass | 11,406 | 13,324 | +17% | 1 | 1 | 0% | 1,083 | 2,546 | +135% | 0 | 0 | — |
case-12 | pass→pass | 13,090 | 7,519 | -43% | 1 | 1 | 0% | 1,142 | 1,301 | +14% | 0 | 0 | — |
case-18 | fail→fail | 19,269 | 11,976 | -38% | 1 | 1 | 0% | 1,828 | 2,103 | +15% | 0 | 0 | — |
case-19 | fail→fail | 15,822 | 7,907 | -50% | 1 | 1 | 0% | 1,682 | 1,399 | -17% | 0 | 0 | — |
case-20 | fail→fail | 2,361 | 23,405 | +891% | 1 | 1 | 0% | 317 | 2,170 | +585% | 0 | 0 | — |
case-21 | pass→pass | 12,530 | 19,036 | +52% | 1 | 1 | 0% | 2,278 | 3,265 | +43% | 0 | 0 | — |
case-04 | fail→pass | 5,332 | 9,848 | +85% | 1 | 1 | 0% | 936 | 2,095 | +124% | 0 | 0 | — |
case-05 | fail→pass | 13,071 | 10,648 | -19% | 1 | 1 | 0% | 1,955 | 1,954 | -0% | 0 | 0 | — |
case-06 | fail→fail | 13,940 | 7,682 | -45% | 1 | 1 | 0% | 2,481 | 2,378 | -4% | 0 | 0 | — |
case-07 | fail→pass | 36,869 | 2,563 | -93% | 1 | 1 | 0% | 6,370 | 1,364 | -79% | 0 | 0 | — |
case-08 | fail→pass | 13,857 | 9,592 | -31% | 1 | 1 | 0% | 1,314 | 2,320 | +77% | 0 | 0 | — |
case-13 | fail→fail | 14,566 | 3,689 | -75% | 1 | 1 | 0% | 2,551 | 1,554 | -39% | 0 | 0 | — |
case-14 | pass→pass | 9,233 | 9,173 | -1% | 1 | 1 | 0% | 1,549 | 2,259 | +46% | 0 | 0 | — |
case-15 | fail→pass | 21,742 | 16,035 | -26% | 1 | 1 | 0% | 2,766 | 2,674 | -3% | 0 | 0 | — |
case-16 | fail→pass | 20,439 | 12,571 | -38% | 1 | 1 | 0% | 2,043 | 1,908 | -7% | 0 | 0 | — |
case-17 | fail→pass | 9,917 | 3,213 | -68% | 1 | 1 | 0% | 1,602 | 1,496 | -7% | 0 | 0 | — |
case-22 | pass→fail | 9,180 | 8,696 | -5% | 1 | 1 | 0% | 1,163 | 1,232 | +6% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +36 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.