GBrain Skillpack JTBD Map

Product Frame

gbrain's skills turn a database and MCP server into a knowledge-work operating system. The 43 local SKILL.md files define how agents should ingest, query, enrich, publish, maintain, research, and operationalize memory.

The pattern is "thin harness, fat skills": deterministic TypeScript handles storage/search/sync, while skill files encode workflows, quality bars, routing, and judgment.

Skill Families

1. Always-On Brain Behavior

Skills: signal-detector, brain-ops.

Job: make every conversation improve the brain without forcing the user to remember capture hygiene.

Product spec:

• Detect entities, ideas, original thinking, and follow-up signals.
• Search brain before external APIs when prior context matters.
• Run read-enrich-write loops so responses create durable context.

2. Setup, Health, and Operations

Skills: install, setup, skillpack-check, smoke-test, maintain, testing, migrate, frontmatter-guard, citation-fixer.

Job: keep the brain running, coherent, and trustworthy.

Product spec:

• Verify environment, migrations, MCP registration, and skills.
• Audit stale pages, malformed frontmatter, missing citations, orphan links, dead links, and tag consistency.
• Run tests and smoke checks before relying on memory in high-value workflows.

3. Ingestion and Capture

Skills: ingest, idea-ingest, media-ingest, voice-note-ingest, meeting-ingestion, article-enrichment, archive-crawler, webhook-transforms, cold-start.

Job: convert messy real-world inputs into structured, searchable brain pages.

Product spec:

• Route by input type instead of asking the user to choose a workflow.
• Preserve exact phrasing for voice notes.
• Extract people, companies, concepts, timelines, quotes, and links.
• Enrich raw article/media dumps with summaries and why-it-matters analysis.
• Protect archives with explicit scan path configuration before crawling.

4. Research and Synthesis

Skills: book-mirror, strategic-reading, concept-synthesis, perplexity-research, academic-verify, data-research, cross-modal-review.

Job: make research personal, evidence-backed, and action-oriented.

Product spec:

• Compare new material against the user's existing brain.
• Separate what is new from what is already known.
• Preserve citations and methodology.
• Turn books/articles/cases into applied playbooks.
• Verify claims through source, method, data, and replication.

5. Retrieval and Knowledge Shaping

Skills: query, enrich, repo-architecture, functional-area-resolver, soul-audit.

Job: retrieve and improve knowledge without flattening it into generic summaries.

Product spec:

• Say "the brain does not have info" when evidence is absent.
• Route pages to correct architecture by subject, not input format.
• Enrich people/company pages with compiled truth and timelines.
• Resolve functional areas so content lands where future agents can find it.

6. Daily Workflow and Publishing

Skills: daily-task-manager, daily-task-prep, briefing, cron-scheduler, reports, publish, brain-pdf.

Job: turn memory into daily execution.

Product spec:

• Store tasks as searchable brain pages.
• Prepare for meetings with attendee and thread context.
• Generate briefings, reports, and PDFs from brain content.
• Publish selected pages as protected HTML.
• Schedule recurring maintenance and briefing flows.

7. Agent and Skill Meta-System

Skills: minion-orchestrator, ask-user, skill-creator, skillify.

Job: let the brain create or coordinate new workflows.

Product spec:

• Ask the user only when a missing decision blocks progress.
• Convert repeated workflows into skills.
• Coordinate sub-work with bounded roles and clear outputs.
• Preserve skill quality so workflow knowledge remains executable.

Persona Map

Key Product Insight

gbrain does not win by being a better notes app. It wins by making memory operational. The skillpack says: when an agent knows something, it should know where that fact lives, how confident it is, how it connects, and when to write the next update.