By Raven-Scout
Automate daily knowledge management by monitoring Slack, Calendar, Linear, and GitHub, synthesizing findings into a persistent knowledge base, and delivering actionable briefings and action items via scheduled Claude Code sessions.
Run an interactive Scout meta-review — a system-level audit that sits above the individual session types. Checks whether sessions are running, mistake audit is trending well, proposals are flowing, KB files are healthy, and data-source coverage is consistent across session types. Runs in the current conversation.
First-time install of Scout. Detects connected tools, collects user details, and hands off to scoutctl bootstrap install. For upgrading an existing vault, run /scout-update.
Show the current state of your Scout installation — config, last runs, KB health, pending proposals, and wishlist status.
Upgrade an existing Scout vault to the current plugin version. Idempotent — re-runs converge to the same state. For first-time install, run /scout-setup.
Interactive work session — walks through today's actionable items one at a time, presents a recommended action with draft content, and executes each one only with explicit approval. Runs in the current conversation (not as a background session).
Launch a Scout morning briefing session as a background process. Auto-detects mode (morning briefing, consolidation, or weekend briefing) from the current time and day.
Launch a Scout consolidation session as a background process. Runs a lighter delta scan — captures what changed since the last run and updates action items and KB.
Launch a Scout dreaming session as a background process. Processes feedback, does KB deep work, and works on wishlist items.
Launch a Scout research session as a background process. Goes outward — discovers new information about KB entities via web search, docs, and APIs, then integrates findings.
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The autonomous daily briefing that cross-checks all your work tools — so nothing falls through the cracks, and you can trust what it surfaces.
Scout runs unattended as scheduled Claude Code sessions. It reads Slack, Calendar, Gmail, Linear, GitHub, and meeting transcripts; cross-checks every finding against the others; and each morning hands you a short list of what actually needs you — every item tagged by how many sources confirm it. What you get is a persistent, interlinked knowledge base you can browse in Obsidian, and a daily action list you can trust because you can see its work.
You shouldn't have to manually reconcile what happened across seven tools yesterday, what's still pending from last week, or what changed while you were in meetings. Scout does it — and when your tools disagree, it flags the contradiction instead of quietly picking a side.
Readable-markdown memory, scheduled runs, and a self-improvement loop are table stakes now — every serious agent has them. Scout's difference is what it does before it tells you anything:
verified (2+ sources), single-source, unverified, stale, or contradicted. You always know how much weight to give it.Most assistants summarize. Scout corroborates — and that's the difference between output you skim and output you act on.
Most "AI memory" tools are static: they store what you tell them and answer when asked. Scout is the opposite — a system that operates and improves on its own, between your check-ins. This is the part other tools don't have, and it's why Scout gets more reliable the longer it runs.
When Scout gets something wrong and you flag it (a 👎 or a one-line correction on its summary), it records a numbered mistake pattern: the error type, the root cause, and the fix. Patterns track recurrence — and if one marked "fixed" happens again, it's flagged as a regression so it can't quietly rot. The fix is written back into Scout's own instructions, so that whole class of error gets rarer over time. (The author's live vault carries 100+ logged patterns.) This isn't a bug tracker; it's a self-model that makes Scout monotonically more reliable.
Scout doesn't wait for a maintainer to ship an update. Its nightly Dreaming session edits its own skill files directly for additive, feedback-aligned fixes, and files an opt-out proposal for anything larger (it applies after a few days unless you reject it). Every change is a separate git commit you can read and git revert — so the safety model is transparency + reversibility, not a checkpoint on every step. (Scout once proposed retiring its own approval gate because it was causing missed-update regressions; the author reviewed the proposal and approved it.)
Scout keeps a Wishlist of improvements and works it down on its own — picking an item each evening, implementing it, shipping it, marking it done. Features Scout has built for itself this way include a native macOS Control Center app, a terminal action-items UI, and the Research session type. You aren't the only one filing feature requests.
A research queue lets Scout expand its own knowledge between briefings — scoring which entities are stale or thin, rotating across your projects so it doesn't fixate on one, then digging via web search, docs, and your tools. Leave a note anywhere in the vault (an inline //==<< … >>==// comment) and the next run picks it up and prioritizes it.
Scout can't see everything from your tools, so it occasionally surfaces a targeted, low-stakes question to fill a gap (always with a link and a one-line gist — never a notification firehose). Your answer is routed into the knowledge graph, and the same question is never asked twice.
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