Workspace Strategy

Strategize about workspace documents: $ARGUMENTS

$ARGUMENTS should be one of:

• "roadmap" — Generate a content roadmap based on gaps and priorities
• "agentic" — Design agentic workflows for the workspace system
• "context" — Plan context coding architecture for docs
• "research" — Identify research priorities and plan investigations
• "reflect" — Reflect on current state, progress, and direction
• A specific question or topic — Answer strategically
• Empty — Ask the user what they want to think through

Context: What This Workspace Is

The workspace at /workspace is an authenticated collaborative area where Brad Brisco and collaborators work with documents. It's backed by markdown files in docs/workspace/ organized into sections (sidebar order is defined in WORKSPACE_SECTION_ORDER in src/lib/workspace/docs.ts):

The frontend reads this via src/lib/workspace/docs.ts → API route → React Query hook → sidebar + doc viewer.

Mode 1: Content Roadmap

When asked for a roadmap, analyze the current workspace state and propose what to create next.

Step 1: Audit current coverage

Read the EEAT theme taxonomy from docs/workspace/insights/eeat-content-pipeline.md and cross-reference against what exists:

# Count articles per theme
grep -r "themes:" docs/workspace/articles/ | sort

Map each Tier 1 theme to its article coverage:

• missional-ecclesiology — How many articles?
• church-planting-multiplication — How many?
• covocational-ministry — How many?
• missional-living-practice — How many?
• neighborhood-place — How many?

Step 2: Read the gap analysis

Read docs/workspace/insights/gap-analysis.md for identified opportunities.

Step 3: Read the content ideas

Read docs/workspace/ideas/platform-content-ideas.md for brainstormed topics.

Step 4: Propose roadmap

Present a prioritized list:

## Content Roadmap

### High Priority (fills a theme gap)
1. [Article] Title — theme, why it matters
2. [Research] Topic — what it enables

### Medium Priority (deepens existing themes)
3. [Article] Title — theme, builds on X
4. [Project] Title — what it coordinates

### Low Priority (nice to have)
5. ...

For each item, note:

• Which section it belongs in
• Which themes it serves
• What existing workspace docs it connects to
• Whether it needs research first

Mode 2: Agentic Workflow Design

When asked about agentic design, think about how AI agents and automated workflows interact with the workspace.

Key questions to explore:

1. Agent-as-author — How should AI Lab or custom agents use workspace docs as context? What docs should be in their retrieval corpus?

2. Agent-as-researcher — How can agents produce research notes that land in research/ and inform future articles?

3. Content pipeline automation — What steps of the authoring workflow (research → outline → draft → review → publish) can be agent-assisted?

4. Cross-reference intelligence — How can agents suggest connections between docs, flag contradictions, or identify gaps?

5. Workspace as agent context — How should the workspace feed into system prompts? Which sections are "always-on" context vs. retrieved on demand?

Design principles:

• Docs are the interface — Agents read and write markdown. No custom data formats.
• Human-in-the-loop — Agents propose; humans approve. Drafts go to status: draft.
• Voice fidelity — Every agent that writes content must load the voice identity first.
• Single source of truth — Workspace docs are canonical. Don't duplicate in vector stores without a sync strategy.

Output format:

Present designs as:

1. Workflow diagram (text-based, showing steps and decision points)
2. Agent capabilities needed (what tools, what context, what guardrails)
3. Implementation plan (which skills/routes/hooks to build)

Mode 3: Context Coding Architecture

When asked about context coding, plan how the workspace integrates with the broader codebase and CLAUDE.md system.

Key concerns:

1. What should CLAUDE.md know about the workspace? — Add workspace awareness to project instructions so Claude always knows the docs exist.

2. Workspace docs as development context — Which workspace docs should inform feature development? (e.g., voice identity informs AI Lab, EEAT pipeline informs content routes)

3. Doc-to-code traceability — How do workspace strategy docs connect to actual implementation? (e.g., gap analysis → new article page → new API route)

4. Skill composition — How do workspace skills (workspace-author, workspace-organize, workspace-strategy) compose with platform skills (new-page, type-safety-chain, etc.)?

5. Memory integration — What workspace learnings should be saved to auto-memory vs. kept as workspace docs?

Decision framework:

Output format:

Present as:

1. Current state — What context is available where
2. Gaps — What's missing or misplaced
3. Proposed changes — Specific files to create/modify
4. Implementation order — What depends on what

Mode 4: Research Priorities

When asked about research, identify what needs investigation and plan the approach.

Research categories:

1. Theological foundations — Scripture study, doctrine exploration, framework development for workspace content
2. Literature review — Academic and practitioner sources that support or challenge Brad's positions
3. Market/audience research — Who reads covocational content? What questions do they have? What's trending?
4. Platform research — What features would serve the workspace? What do similar platforms do?
5. Competitive landscape — What content exists elsewhere on these topics? Where are the gaps?

Research process:

1. Define the question — What specifically do we need to know?
2. Check the corpus first — Search books and existing workspace docs
3. External search — Use WebSearch for current sources, statistics, perspectives
4. Synthesize — Write a research note in docs/workspace/research/
5. Connect — Link the research to specific content opportunities

Output format:

## Research Priority: [Topic]

**Question:** What do we need to know?
**Why it matters:** What content or decisions depend on this?
**Existing corpus coverage:** What Brad has already written about this
**External sources to investigate:** Specific searches or databases
**Target output:** Research note → informs [article/project/course]
**Estimated effort:** Quick (1 search) / Medium (multiple sources) / Deep (multi-session)

Mode 5: Reflect

When asked to reflect, take stock of the workspace as a whole.

Reflection prompts:

1. Coverage — Are the 5 Tier 1 themes adequately covered? Which is weakest?
2. Voice consistency — Do existing articles consistently hit all 5 voice markers?
3. Organizational clarity — Does the current section layout still make sense? Should anything move?
4. Freshness — Are there docs that are stale or outdated?
5. Actionability — Do project docs have clear next steps? Are task lists up to date?
6. Connections — Are there docs that should reference each other but don't?
7. Frontend quality — Does the workspace render all docs cleanly? Any typography issues?

Reflection output:

Present as a brief (under 500 words) assessment with:

• Strengths — What's working well
• Gaps — What's missing or weak
• Recommendations — 3-5 specific next actions, each linked to a skill or command

Composing with Other Skills

This skill works best in sequence with:

• /workspace-author — After identifying gaps, write the content
• /workspace-organize — After planning new sections, audit the structure
• /author-research — For deep external research on specific topics
• /article-plan — For detailed article planning before authoring

Things to Never Do

• Never propose changes to docs/internal/ or engineering docs — that's a different domain
• Never recommend content without checking what already exists
• Never plan without grounding in the EEAT theme taxonomy
• Never ignore the voice identity when recommending content direction
• Never propose agentic workflows that bypass human review for published content