Portable personal context for AI tools, stored in plain Markdown files you own.
People often repeat their history, preferences, goals, and constraints across AI tools and sessions. SelfContext keeps that context in a local, inspectable vault that you can edit, copy, back up, and carry between models.
SelfContext is not a hosted app or a separate AI runtime. It provides
project-local skills for an existing AI tool that supports Agent Skills; the
local vault/ remains the source of truth.
The core vault lifecycle and focused context areas are implemented. Future work is tracked as experiments in the Roadmap, not promises.
SelfContext works with an AI tool that can load project-local Agent Skills. No server or dependency installation is needed for normal use.
git clone https://github.com/joacod/self-context.git
cd self-contextOpen the repository root in your AI tool and use natural language:
ingest my resume into SelfContext
what does my context say about a skill or experience?
review my context for stale or conflicting information
help me position myself for a role based on my context
On first use, SelfContext initializes a missing vault/ automatically. If you
already have a vault, place it at vault/; the skill will orient itself from
the vault's own files. No custom CLI is required.
After updating SelfContext, update the repository and ask your AI tool:
git pullupgrade vault latest
SelfContext is latest-first. After updating the repository, run
upgrade vault latest to bring an existing vault to the current model before
normal use. The upgrade checks your existing vault and applies only the updates
it needs, including supported format changes, relevant context areas, and safe
organization improvements. Existing evidence and history are preserved, and
ambiguous decisions are left for review. If your vault is already current,
nothing is changed.
You
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v
Existing AI tool + model
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v
SelfContext skills
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v
Local Context Vault
(Markdown + YAML frontmatter + standard links)
- The vault is the durable source of truth. You can inspect, edit, copy, and back it up independently.
- The existing AI tool provides the model and execution. SelfContext provides workflows for ingest, query, review, lint, advice, and maintenance.
- User-stated facts, source-derived facts, agent inferences, and derived analyses remain distinguishable.
- Portable storage: ordinary Markdown, YAML frontmatter, and standard relative links.
- Natural-language workflows: ingest, query, targeted review, structural validation, and keeping an existing vault current.
- Trustworthy context: provenance, freshness, unresolved items, contradictions, and explicit confirmation for important inferences.
SelfContext organizes durable context into focused areas such as Career, Learning, Writing, Relationships, Media / Taste, and Ventures / Projects. It uses the areas relevant to your context as needed.
| Vertical | Vault area | Focus |
|---|---|---|
| Career | career/ |
Career evidence and concepts |
| Learning | learning/ |
Knowledge states, gaps, corrections, and progression |
| Writing | writing/ |
Evidence-backed communication and writing context |
| Relationships | relationships/ |
Shared history, commitments, and open loops |
| Media / Taste | media/ |
Reactions to cultural works and evolving taste |
| Ventures / Projects | ventures/ |
Initiative lifecycle, decisions, commitments, evidence, and outcomes |
- Obsidian: use
vault/as an Obsidian vault if you want a visual editor. Obsidian is optional.
vault/is local and Git-ignored. Never commit it or force-add files from it.- The canonical format remains useful without SelfContext, a particular model, AI tool, search implementation, or Obsidian.
- Git ignore helps prevent accidental commits, but it does not prevent a model or provider from seeing information you give its tool.
- No hosted service, database, embeddings, telemetry, background service, or custom runtime is required.
- Vision: the problem, thesis, and design commitments.
- Architecture: system boundaries, lifecycle, and vault structure.
- Roadmap: the implemented foundation and future experiments.
For repository rules and skill changes, see Repository guidance and Skill maintenance.
From the repository root, run the canonical dependency-free validation:
python3 scripts/validate_repo.pyOperational migration and maintenance procedures live under the SelfContext skill references.
Licensed under the MIT License.