Lateral

Build the following focused alternative to Lateral. This is a deliberately limited personal or small-team substitute, not parity with the paid service.

WORKING SLICE
Compare uploaded papers in an evidence matrix covering question, method, sample and result, with every cell linked to a source excerpt.

SETUP AND ARCHITECTURE
Use Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook. Prerequisites: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success.

DOMAIN MODEL AND INVARIANTS
Store Paper, SourcePage, MatrixColumn, EvidenceCell and ReviewerDecision; blank/unknown cells remain distinct from negative findings and a quote cannot move silently after re-extraction.

IMPLEMENTATION CONTRACT
Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content.

APP-SPECIFIC BOUNDARY AND RECOVERY
Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.

ACCEPTANCE SCENARIO
Compare a paper reporting no effect with one missing the outcome; show 'no effect reported' versus 'not found' and link the first to its actual page. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested.

DELIVERY
Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product.

PROJECT RULES FOR AGENTS.md
Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.

# AGENTS.md — Build guide for Lateral

## Project scope
Compare uploaded papers in an evidence matrix covering question, method, sample and result, with every cell linked to a source excerpt.

Catalogue verdict: kinda. The visible research workspace loop is buildable, but a credible replacement needs more than the first screen. Lateral earns its keep through data, import reliability, so expect a weekend or multi-day build and a narrower personal scope.
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
- Runtime and tools: Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook.
- Before starting: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider.

## Stack and architecture
- Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook
- Data design: Store Paper, SourcePage, MatrixColumn, EvidenceCell and ReviewerDecision; blank/unknown cells remain distinct from negative findings and a quote cannot move silently after re-extraction.
- Setup: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider

## Security and data integrity
- Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims.
- Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.
- Keep secrets outside client bundles and exported projects; document what leaves the device and make retention/deletion controls visible.

## Agent implementation rules
- Project rule — domain: Store Paper, SourcePage, MatrixColumn, EvidenceCell and ReviewerDecision; blank/unknown cells remain distinct from negative findings and a quote cannot move silently after re-extraction.
- Project rule — scope and recovery: Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.
- Project rule — acceptance: Compare a paper reporting no effect with one missing the outcome; show 'no effect reported' versus 'not found' and link the first to its actual page.
- Project rule — delivery: document real setup commands and permissions; do not claim a build, accuracy level, performance result or security certification that has not been demonstrated.

## Optional agent skills and references
- Recommended skill: [modern-python](https://github.com/trailofbits/skills/blob/main/plugins/modern-python/skills/modern-python/SKILL.md) — structure the Python worker or explicitly optional read-only utility with pinned dependencies, typed boundaries and clear failure handling. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
- Recommended skill: [web-design-guidelines](https://github.com/vercel-labs/agent-skills/blob/main/skills/web-design-guidelines/SKILL.md) — review keyboard access, focus, validation, error recovery and the readable work/review interface or HTML report. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
- Recommended skill: [pdf](https://github.com/anthropics/skills/blob/main/skills/pdf/SKILL.md) — inspect PDF source/extraction or generated report layout in the workflow; check the skill license and required PDF/OCR binaries. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.

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 this working slice using synthetic or explicitly authorized non-sensitive examples: Compare uploaded papers in an evidence matrix covering question, method, sample and result, with every cell linked to a source excerpt.
- Share a synthetic example export and the acceptance walkthrough; keep real customer, health, financial and source data private: Compare a paper reporting no effect with one missing the outcome; show 'no effect reported' versus 'not found' and link the first to its actual page.
- State the limits before asking someone to replace their existing tool: Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.

## Engineering roadmap
1. Phase 1 — Pin the working slice and create its example input: Compare uploaded papers in an evidence matrix covering question, method, sample and result, with every cell linked to a source excerpt. Confirm setup: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider.
2. Phase 2 — Implement persistence and write-time invariants before decorating the UI: Store Paper, SourcePage, MatrixColumn, EvidenceCell and ReviewerDecision; blank/unknown cells remain distinct from negative findings and a quote cannot move silently after re-extraction.
3. Phase 3 — Connect the working view to real saved state. Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims.
4. Phase 4 — Expose the app-specific limits and recovery path in context: Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.
5. Phase 5 — Walk through this concrete acceptance case and preserve its exported evidence: Compare a paper reporting no effect with one missing the outcome; show 'no effect reported' versus 'not found' and link the first to its actual page. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.

## Paid-product capabilities outside this build
- publisher-specific import reliability
- citation graph scale
- team libraries and institutional access
- licensed scholarly metadata

## Implementation prompt
Build the following focused alternative to Lateral. This is a deliberately limited personal or small-team substitute, not parity with the paid service.

WORKING SLICE
Compare uploaded papers in an evidence matrix covering question, method, sample and result, with every cell linked to a source excerpt.

SETUP AND ARCHITECTURE
Use Python, SQLite FTS5, a PDF/text extraction worker and a React evidence notebook. Prerequisites: User-owned or licensed source documents, a local data folder and an optional explicitly configured model provider. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success.

DOMAIN MODEL AND INVARIANTS
Store Paper, SourcePage, MatrixColumn, EvidenceCell and ReviewerDecision; blank/unknown cells remain distinct from negative findings and a quote cannot move silently after re-extraction.

IMPLEMENTATION CONTRACT
Preserve source hashes, page/section anchors and exact quotations. OCR and optional generated summaries are derived views, never replacements for originals; label missing text and unsupported claims. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content.

APP-SPECIFIC BOUNDARY AND RECOVERY
Start with manually reviewed extraction and limited corpus search. Do not extrapolate sample findings or fabricate a completed systematic review from an automated matrix.

ACCEPTANCE SCENARIO
Compare a paper reporting no effect with one missing the outcome; show 'no effect reported' versus 'not found' and link the first to its actual page. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested.

DELIVERY
Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product.

PROJECT RULES FOR AGENTS.md
Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.

## 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.