# AGENTS.md — Build guide for WriterZen

## Project scope
Import a keyword list, group it using an explicit rule, prepare an evidence-backed article outline and draft sections from user-supplied sources.

Catalogue verdict: kinda. The core loop is buildable, but a dependable replacement becomes a real weekend or multi-day project. For WriterZen, cluster keywords, prepare a brief, and manage an article through a structured content workflow. The hard boundary is keyword data sources, clustering logic, plagiarism services, and collaboration, plus workflow, data, and model tuning.
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- Do not publish, spend money, contact customers, delete source data or run irreversible migrations without the project owner's authorization.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 KeywordSource, ClusterRule, ClusterMembership, Brief and SourceClaim; search volume is stored only when supplied with provenance and clustering decisions remain editable.
- 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 reviewed keyword imports and transparent grouping. No ranking guarantee, auto-generated authority or fabricated citations; draft publication requires factual and originality review.
- 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 KeywordSource, ClusterRule, ClusterMembership, Brief and SourceClaim; search volume is stored only when supplied with provenance and clustering decisions remain editable.
- Project rule — scope and recovery: Start with reviewed keyword imports and transparent grouping. No ranking guarantee, auto-generated authority or fabricated citations; draft publication requires factual and originality review.
- Project rule — acceptance: Two near-identical keywords imply different intent and one has no volume; allow separate clusters and show unknown volume instead of inventing demand.
- 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.

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: Import a keyword list, group it using an explicit rule, prepare an evidence-backed article outline and draft sections from user-supplied sources.
- Share a synthetic example export and the acceptance walkthrough; keep real customer, health, financial and source data private: Two near-identical keywords imply different intent and one has no volume; allow separate clusters and show unknown volume instead of inventing demand.
- State the limits before asking someone to replace their existing tool: Start with reviewed keyword imports and transparent grouping. No ranking guarantee, auto-generated authority or fabricated citations; draft publication requires factual and originality review.

## Engineering roadmap
1. Phase 1 — Pin the working slice and create its example input: Import a keyword list, group it using an explicit rule, prepare an evidence-backed article outline and draft sections from user-supplied sources. 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 KeywordSource, ClusterRule, ClusterMembership, Brief and SourceClaim; search volume is stored only when supplied with provenance and clustering decisions remain editable.
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 reviewed keyword imports and transparent grouping. No ranking guarantee, auto-generated authority or fabricated citations; draft publication requires factual and originality review.
5. Phase 5 — Walk through this concrete acceptance case and preserve its exported evidence: Two near-identical keywords imply different intent and one has no volume; allow separate clusters and show unknown volume instead of inventing demand. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.

## Paid-product capabilities outside this build
- keyword data sources, clustering logic, plagiarism services, and collaboration
- proprietary ranking data
- brand-trained models
- team workflows
- large template libraries

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

WORKING SLICE
Import a keyword list, group it using an explicit rule, prepare an evidence-backed article outline and draft sections from user-supplied sources.

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 KeywordSource, ClusterRule, ClusterMembership, Brief and SourceClaim; search volume is stored only when supplied with provenance and clustering decisions remain editable.

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 reviewed keyword imports and transparent grouping. No ranking guarantee, auto-generated authority or fabricated citations; draft publication requires factual and originality review.

ACCEPTANCE SCENARIO
Two near-identical keywords imply different intent and one has no volume; allow separate clusters and show unknown volume instead of inventing demand. 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.