# AGENTS.md — Build guide for Mem

## Project scope
Capture notes quickly, search text and optionally local embeddings, and show related notes with an explanation of the matching passages. Keep Markdown files portable and suggestions separate from authored content.

Catalogue verdict: kinda. The core loop is buildable, but a dependable replacement becomes a real weekend or multi-day project. For Mem, capture notes quickly and retrieve them through semantic search and related-memory suggestions. The hard boundary is hosted ai memory, sync, ingest integrations, and continuously tuned retrieval, plus sync, collaboration, and capture polish.
Use the implementation prompt below to define the deliverable. Complete each phase's acceptance checks before extending the scope.

## Working agreement
- Inspect the repository and its existing instructions before choosing paths, dependencies or commands. Keep one coherent stack and explain changes to the proposed architecture.
- Plan a vertical slice that accepts a real input and produces the useful output described below. Persist only the state the prompt calls for; respect memory-only and upstream-managed workflows. Use fixtures only when they are clearly labelled.
- After scaffolding, document the actual install, development, check and build commands in README and keep them synchronized with the package or project manifest. Do not report commands as successful unless they ran.
- Work in small steps. At handoff, list implemented flows, checks actually performed, remaining blockers, and any credentials or provider setup the owner must supply.
- Do not publish, spend money, contact customers, delete source data or run irreversible migrations without the project owner's authorization.

## Prerequisites
- Node and the Rust toolchain, a supported desktop build environment and an explicitly selected data folder. Remote sync is outside the initial scope.
- Implementation components: Tauri, React and TypeScript for the desktop interface with a narrowly scoped Rust filesystem bridge. SQLite for structured state and search; user-owned files for original documents and attachments.
- Scope boundary: hosted AI memory, sync, ingest integrations, and continuously tuned retrieval; frictionless mobile capture

## Stack and architecture
- Tauri, React and TypeScript for the desktop interface with a narrowly scoped Rust filesystem bridge.
- SQLite for structured state and search; user-owned files for original documents and attachments.
- Domain model: notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback

## Security and data integrity
- Limit Tauri capabilities to selected folders and commands. Render imported content without executable HTML, and never expose arbitrary shell execution to the webview.
- Correctness boundary: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
- Save edits atomically with stable IDs and revision history. Detect external file changes and offer a conflict copy instead of last-write-wins data loss.
- Provide a portable folder export with a JSON manifest and original files. Restore to a separate folder; rebuild disposable indexes from sources.

## Agent implementation rules
- Project rule — data model: notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback
- Project rule — preserve this invariant: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
- Project rule — acceptance evidence: Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown.

## Optional agent skills and references
- Optional external skill: [vercel-react-best-practices](https://github.com/vercel-labs/agent-skills/blob/main/skills/react-best-practices/SKILL.md) — Improve React and Next.js data fetching, rendering, bundle size and server performance. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
- Optional external skill: [web-design-guidelines](https://github.com/vercel-labs/agent-skills/blob/main/skills/web-design-guidelines/SKILL.md) — Review web interfaces for accessibility, keyboard focus, forms, navigation and interaction quality. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
- Optional external skill: [sharp-edges](https://github.com/trailofbits/skills/blob/main/plugins/sharp-edges/skills/sharp-edges/SKILL.md) — Review security-sensitive APIs and configuration for dangerous defaults and easy-to-misuse interfaces. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.

Read the linked SKILL.md and its dependencies before adding a skill. Select only the skills matching this project's runtime and task; their documentation does not supply API access, credentials or approval to perform external actions. Pin the reviewed revision where the tool supports it. Follow the chosen agent's documented project-level installation mechanism.

## Distribution ideas
These are optional planning notes. Obtain the owner's approval before publishing or contacting anyone.
- Demonstrate the actual Mem-inspired workflow with owned or clearly labeled sample data: Capture notes quickly, search text and optionally local embeddings, and show related notes with an explanation of the matching passages. Keep Markdown files portable and suggestions separate from authored content.
- Publish a reproducible walkthrough with this observable result: Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown.
- Explain who can operate this scoped tool, its setup and ongoing costs, and these remaining product gaps: hosted AI memory, sync, ingest integrations, and continuously tuned retrieval; frictionless mobile capture Avoid guaranteed savings, performance scores or implied endorsement.

## Engineering roadmap
1. Phase 1 — Scope and fixtures. Implement this bounded workflow: Capture notes quickly, search text and optionally local embeddings, and show related notes with an explanation of the matching passages. Keep Markdown files portable and suggestions separate from authored content. Record prerequisites, select representative user-owned fixtures and document the unsupported features: hosted AI memory, sync, ingest integrations, and continuously tuned retrieval; frictionless mobile capture
2. Phase 2 — Durable model. Model notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback Add migrations or a versioned document format, explicit validation, stable IDs and a visible import-error report. Preserve this rule: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
3. Phase 3 — Complete the first useful path. Implement the workflow's input, review and output interface, with clear controls and explicit empty/error states. Save edits atomically with stable IDs and revision history. Detect external file changes and offer a conflict copy instead of last-write-wins data loss.
4. Phase 4 — Permissions and integration failure. Limit Tauri capabilities to selected folders and commands. Render imported content without executable HTML, and never expose arbitrary shell execution to the webview. Request integration credentials and permissions only for the enabled feature; show a disconnected state instead of mock results.
5. Phase 5 — Portable handoff. Provide a portable folder export with a JSON manifest and original files. Restore to a separate folder; rebuild disposable indexes from sources. Include setup, operating limits, fixture walkthrough and shutdown/restart instructions in the README.
6. Phase 6 — Acceptance scenarios. Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown. Repeat the workflow after restart and with a denied permission or unavailable dependency; show recoverable failure rather than a success placeholder.

## Paid-product capabilities outside this build
- hosted AI memory, sync, ingest integrations, and continuously tuned retrieval
- frictionless mobile capture
- real-time team editing
- hosted publishing
- proprietary AI memory

## Implementation prompt
WORKING SLICE
Capture notes quickly, search text and optionally local embeddings, and show related notes with an explanation of the matching passages. Keep Markdown files portable and suggestions separate from authored content.

Build this scoped Mem-inspired workflow with a documented data model and visible failure states.

Architecture
- Tauri, React and TypeScript for the desktop interface with a narrowly scoped Rust filesystem bridge.
- SQLite for structured state and search; user-owned files for original documents and attachments.

Prerequisites and limits
Node and the Rust toolchain, a supported desktop build environment and an explicitly selected data folder. Remote sync is outside the initial scope.
Outside this release: hosted AI memory, sync, ingest integrations, and continuously tuned retrieval; frictionless mobile capture

Data model and correctness
notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback
Invariant: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
Save edits atomically with stable IDs and revision history. Detect external file changes and offer a conflict copy instead of last-write-wins data loss.

Security and privacy
Limit Tauri capabilities to selected folders and commands. Render imported content without executable HTML, and never expose arbitrary shell execution to the webview.

Recovery and export
Provide a portable folder export with a JSON manifest and original files. Restore to a separate folder; rebuild disposable indexes from sources.

Implementation order
1. Phase 1 — Scope and fixtures. Implement this bounded workflow: Capture notes quickly, search text and optionally local embeddings, and show related notes with an explanation of the matching passages. Keep Markdown files portable and suggestions separate from authored content. Record prerequisites, select representative user-owned fixtures and document the unsupported features: hosted AI memory, sync, ingest integrations, and continuously tuned retrieval; frictionless mobile capture
2. Phase 2 — Durable model. Model notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback Add migrations or a versioned document format, explicit validation, stable IDs and a visible import-error report. Preserve this rule: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
3. Phase 3 — Complete the first useful path. Implement the workflow's input, review and output interface, with clear controls and explicit empty/error states. Save edits atomically with stable IDs and revision history. Detect external file changes and offer a conflict copy instead of last-write-wins data loss.
4. Phase 4 — Permissions and integration failure. Limit Tauri capabilities to selected folders and commands. Render imported content without executable HTML, and never expose arbitrary shell execution to the webview. Request integration credentials and permissions only for the enabled feature; show a disconnected state instead of mock results.
5. Phase 5 — Portable handoff. Provide a portable folder export with a JSON manifest and original files. Restore to a separate folder; rebuild disposable indexes from sources. Include setup, operating limits, fixture walkthrough and shutdown/restart instructions in the README.
6. Phase 6 — Acceptance scenarios. Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown. Repeat the workflow after restart and with a denied permission or unavailable dependency; show recoverable failure rather than a success placeholder.

Acceptance
Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown.
Use real source data or clearly labeled fixtures. Explain unsupported input and provider failures; do not fabricate analytics, delivery receipts, accuracy claims or security guarantees.

Optional agent guidance
Optional external skill: [vercel-react-best-practices](https://github.com/vercel-labs/agent-skills/blob/main/skills/react-best-practices/SKILL.md) — Improve React and Next.js data fetching, rendering, bundle size and server performance. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
Optional external skill: [web-design-guidelines](https://github.com/vercel-labs/agent-skills/blob/main/skills/web-design-guidelines/SKILL.md) — Review web interfaces for accessibility, keyboard focus, forms, navigation and interaction quality. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
Optional external skill: [sharp-edges](https://github.com/trailofbits/skills/blob/main/plugins/sharp-edges/skills/sharp-edges/SKILL.md) — Review security-sensitive APIs and configuration for dangerous defaults and easy-to-misuse interfaces. Review its instructions and compatibility before use; it does not grant deployment, data-access or publication permission.
Project rule — data model: notes, immutable note IDs, links, derived embeddings, source revisions and suggestion feedback
Project rule — preserve this invariant: Embeddings are keyed by content hash and model; semantic similarity is not a factual relationship and cannot silently create links.
Project rule — acceptance evidence: Edit a note and exclude its stale embedding until rebuilt; renaming the note preserves backlinks and a clean export contains original Markdown.

## Completion evidence
Demonstrate the prompt's acceptance scenarios against the scoped workflow. Include setup from a clean checkout and failure recovery. Check persistence across restart and export/restore only for the state the prompt says to store; for memory-only tools, confirm that temporary content is discarded as specified. Record actual results and remaining limitations. A detailed plan alone does not establish a working replacement.