| name | workspace-navigation |
| description | Efficiently navigate and interact with shared agent workspaces and discussion rooms. Use when working in collaborative repositories, organizing thoughts, or coordinating with other agents. Enables structured collaboration without file chaos. |
| triggers | ["navigate the workspace","organize the shared workspace","set up the agent workspace","workspace navigation","how do I structure work in the shared repo","coordinate files across agents"] |
Agent Workspace Navigator Skill
Version: 1.2
Created: 2026-02-11
Author: Tres Pies Design
Purpose: Efficiently navigate and interact with shared agent workspaces and discussion rooms
I. Philosophy
This skill encodes best practices for working in shared agent workspaces—structured repositories where multiple agents collaborate, think together, and build shared context. It provides patterns for reading, writing, and organizing content in a way that maximizes clarity, minimizes token waste, and enables effective collaboration.
Philosophy: A shared workspace is not a file dump—it's a thinking room. Structure enables clarity; clarity enables collaboration.
II. When to Use This Skill
- Working in a shared private repository with other agents
- Contributing to or reading from a collaborative discussion space
- Organizing thoughts, specifications, or research in a structured way
- Coordinating work across multiple agents or sessions
- Building shared context without unstructured file chaos
III. Workspace Structure & Workflows
A well-structured agent workspace follows the Planning with Files philosophy and organizes content by purpose, not by time or author.
Standard Directory Structure
workspace/
├── README.md # Workspace overview and navigation guide
├── 00_Active/ # Current work in progress
│ ├── discussions/ # Active discussions and threads
│ ├── drafts/ # Work in progress (not final)
│ ├── decisions/ # Decisions made (with rationale)
│ └── handoffs/ # Pending handoffs between agents
├── 01_Specifications/ # Finalized specs and designs
│ ├── architecture/ # System architecture docs
│ ├── features/ # Feature specifications
│ └── protocols/ # Protocols and standards
├── 02_Research/ # Research findings and synthesis
│ ├── deep-dives/ # Deep research on specific topics
│ ├── landscape-scans/ # Wide research across domains
│ └── references/ # External sources and citations
├── 03_Memory/ # Shared memory and knowledge base
│ ├── seeds/ # Reusable patterns and insights
│ ├── learnings/ # Lessons learned
│ └── context/ # Shared context for continuity
├── 04_Artifacts/ # Generated artifacts and outputs
│ ├── code/ # Code examples or prototypes
│ ├── diagrams/ # Visual artifacts
│ └── documents/ # Final documents
└── 05_Archive/ # Completed or deprecated work
├── by-date/ # Time-based archive
└── by-topic/ # Topic-based archive
File Naming Conventions
Format: YYYY-MM-DD_topic-name_author.md
Examples:
2026-02-11_handoff_protocol_manus.md
2026-02-10_context_compression_cipher.md
2026-02-09_collaboration_protocol_manus-cipher.md
Why:
- Date prefix enables chronological sorting
- Topic name provides context
- Author attribution enables tracking
- Underscore separators are filesystem-friendly
Reading from the Workspace
1. Start with the Index
Always read README.md first to understand:
- Workspace purpose and scope
- Directory structure and conventions
- Active discussions and priorities
- How to contribute
2. Navigate by Purpose, Not Time
Don't:
- Browse chronologically through all files
- Read everything in a directory
Do:
- Identify your purpose (e.g., "understand memory architecture")
- Navigate to the relevant directory (e.g.,
01_Specifications/architecture/)
- Read the most recent or relevant file
3. Use Grep for Targeted Search
Pattern:
grep -r "memory compression" workspace/ --include="*.md"
grep -r "context window" workspace/01_Specifications/ --include="*.md"
grep -r "Author: Cipher" workspace/00_Active/discussions/ --include="*.md"
4. Read Metadata First
Every document should have frontmatter:
---
title: Memory Garden Design
author: Manus
date: 2026-02-02
status: Draft | Active | Final | Archived
tags: [memory, architecture, compression]
related: [context-compression-strategy, seed-extraction]
---
Read the metadata to decide:
- Is this relevant to my current task?
- Is this the most recent version?
- Who authored this, and should I coordinate with them?
- What related documents should I read?
5. Extract Key Insights Efficiently
Don't:
- Read every word of every document
- Copy entire documents into your context
Do:
- Skim for structure (headings, lists, tables)
- Extract key insights (1-3 sentences per section)
- Note open questions or decisions
- Link to the full document for reference
Template:
## Insights from [Document Title]
**Author:** [Name]
**Date:** [YYYY-MM-DD]
**Status:** [Draft/Active/Final]
**Link:** [Path to document]
**Key Insights:**
- [Insight 1]
- [Insight 2]
- [Insight 3]
**Open Questions:**
- [Question 1]
- [Question 2]
**Decisions:**
- [Decision 1: Rationale]
**Relevance to Current Task:**
[How this informs what I'm working on]
Writing to the Workspace
1. Choose the Right Location
Ask:
- Is this work in progress or finalized?
- Is this a discussion, specification, or research?
- Who is the intended audience?
Decision Tree:
Is this finalized?
├─ No → 00_Active/
│ ├─ Is this a discussion? → discussions/
│ ├─ Is this a draft spec? → drafts/
│ ├─ Is this a decision? → decisions/
│ └─ Is this a handoff? → handoffs/
└─ Yes → Where does it belong?
├─ Specification → 01_Specifications/
├─ Research → 02_Research/
├─ Knowledge/Pattern → 03_Memory/
├─ Artifact/Output → 04_Artifacts/
└─ Completed/Deprecated → 05_Archive/
2. Use Structured Templates
Discussion Template
---
title: [Discussion Topic]
author: [Your Name]
date: [YYYY-MM-DD]
status: Active
tags: [tag1, tag2, tag3]
participants: [agent1, agent2]
---
# [Discussion Topic]
## Context
[What is the background or situation that prompted this discussion?]
## Question / Problem
[What are we trying to decide or solve?]
## Perspectives
### Perspective 1: [Name]
[Description of this perspective]
**Pros:**
- [Pro 1]
- [Pro 2]
**Cons:**
- [Con 1]
- [Con 2]
### Perspective 2: [Name]
[Repeat structure]
## Open Questions
- [ ] [Question 1]
- [ ] [Question 2]
## Next Steps
- [ ] [Action 1: Owner]
- [ ] [Action 2: Owner]
## References
- [Link to related discussion]
- [Link to relevant spec]
Specification Template
See specification-writer skill for full template.
Research Template
See research-modes skill for full template.
Decision Template
---
title: [Decision Title]
author: [Your Name]
date: [YYYY-MM-DD]
status: Final
tags: [tag1, tag2, tag3]
decision_id: [Unique ID, e.g., DEC-001]
---
# Decision: [Title]
## Context
[What situation led to this decision?]
## Decision
[What was decided? Be specific and actionable.]
## Rationale
[Why was this decision made?]
**Factors Considered:**
- [Factor 1]
- [Factor 2]
- [Factor 3]
**Alternatives Considered:**
- [Alternative 1: Why rejected]
- [Alternative 2: Why rejected]
## Implications
**Immediate:**
- [Implication 1]
- [Implication 2]
**Long-term:**
- [Implication 1]
- [Implication 2]
## Risks & Mitigations
| Risk | Likelihood | Impact | Mitigation |
|------|------------|--------|------------|
| [Risk 1] | Low/Med/High | Low/Med/High | [How to address] |
## Review Criteria
[How will we know if this decision was correct?]
- [ ] [Criterion 1]
- [ ] [Criterion 2]
## References
- [Link to discussion]
- [Link to research]
3. Write for Clarity and Scannability
Principles:
- Use headings to create structure
- Use lists for enumerations
- Use tables for comparisons
- Use blockquotes for key insights
- Use code blocks for examples
Don't:
- Write long paragraphs without structure
- Bury key insights in prose
- Use vague language ("maybe", "possibly", "might")
Do:
- Make headings descriptive ("Memory Compression Strategy" not "Strategy")
- Put key insights at the top (executive summary)
- Use specific language ("Use 3-month rule" not "Consider time-based compression")
4. Link to Related Content
Always include a "References" or "Related" section to help others navigate.
Format:
## Related Content
**Discussions:**
- [Discussion: Memory Architecture](../00_Active/discussions/2026-02-01_memory-architecture_manus.md)
**Specifications:**
- [Spec: Context Compression](../01_Specifications/architecture/context-compression.md)
**Research:**
- [Research: Semantic Compression Techniques](../02_Research/deep-dives/semantic-compression.md)
**Seeds:**
- [Seed: 3-Month Rule](../03_Memory/seeds/3-month-rule.md)
5. Update the Index
After creating or updating a document, update the workspace README.md to reflect:
- New active discussions
- Completed decisions
- Finalized specifications
- Key research findings
IV. Best Practices: Token Efficiency
1. Surgical Reading
Don't:
- Read entire workspace into context
- Load all files in a directory
Do:
- Read README.md first (500-1000 tokens)
- Identify 2-3 relevant files (2000-5000 tokens each)
- Extract key insights into a summary (500-1000 tokens)
- Total: ~5,000-10,000 tokens vs. 50,000+ tokens
2. Incremental Context Building
Pattern:
- Start with minimal context (README + current task)
- Add context as needed (specific files)
- Compress context after each major milestone
- Archive completed work
3. Reference, Don't Copy
Don't:
- Copy entire documents into your working memory
- Duplicate content across multiple files
Do:
- Link to source documents
- Extract key insights (1-3 sentences)
- Reference by path and section
Example:
As documented in [Memory Architecture Spec](../01_Specifications/architecture/memory.md#compression-strategy), we use the 3-month rule for semantic compression.
4. Use Metadata for Filtering
Before reading a file, check metadata:
- Is this relevant? (tags, title)
- Is this current? (date, status)
- Is this authoritative? (author, decision_id)
This saves:
- Reading time (minutes)
- Token cost (thousands of tokens)
- Context pollution (irrelevant information)
Collaboration Patterns
Pattern 1: Threaded Discussions
Use when: Multiple agents are exploring a topic together
Process:
- Agent A creates initial discussion document in
00_Active/discussions/
- Agent B reads and adds their perspective to the same document
- Agent C reads both perspectives and synthesizes
- When consensus is reached, move to
00_Active/decisions/
Pattern 2: Handoff Pattern
Use when: Work passes between agents
Process:
- Agent A completes work and creates handoff package in
00_Active/handoffs/
- Agent B reviews handoff package
- Agent B accepts or rejects with specific feedback
- Upon acceptance, Agent B moves handoff to their active work
- Upon completion, move to archive with results documented
Pattern 3: Parallel Research
Use when: Multiple agents research different aspects of the same problem
Process:
- Agents agree on research scope and division of labor
- Each agent creates their own research document in
02_Research/
- Agents read each other's findings
- One agent synthesizes into a unified document
- Synthesized document is moved to
03_Memory/ as shared knowledge
Pattern 4: Seed Sharing
Use when: An agent extracts a reusable pattern
Process:
- Agent extracts seed using
seed-extraction skill
- Agent documents seed in
03_Memory/seeds/
- Agent updates seed index in
03_Memory/seeds/README.md
- Other agents can discover and apply the seed
Maintenance Practices
Weekly Review (30 minutes)
Tasks:
- Review
00_Active/ directory
- Move finalized drafts to appropriate directories
- Archive completed discussions
- Update decision log
- Update workspace README.md
- Reflect current priorities
- Update navigation guide
- Compress old discussions
- Extract key insights into memory
- Archive full discussions
Monthly Audit (1-2 hours)
Tasks:
- Review
01_Specifications/ for outdated specs
- Review
03_Memory/ for unused seeds
- Archive deprecated content to
05_Archive/
- Update directory structure if needed
- Refactor for clarity and efficiency
V. Quality Checklist
Before committing content to the workspace, verify:
Structure
Content
Collaboration
Token Efficiency
VI. Example: Dojo Multi-Agent Workspace (February 2026)
The Problem: 3 agents (architect, implementer, reviewer) needed to collaborate on the Dojo Gateway v0.2.0 release across 20+ spec documents, 5 ADRs, and a shared decision log — without stepping on each other's work.
The Process:
- Structure: Established workspace with
specs/, decisions/, scouts/, and drafts/ directories. Each agent had a designated drafts subdirectory.
- Reading: Agents used surgical reading — skim headings first, extract 1-3 key insights per document, reference full paths instead of copying content.
- Writing: All new content included frontmatter (author, date, status). Decisions used the ADR template. Specs used the release-specification template.
- Coordination: Handoff protocol used for agent transitions. Decision propagation tracked which documents were affected by each ADR.
The Outcome: 20 specs and 5 ADRs produced in 10 days with zero file conflicts. Token usage stayed under budget because agents read surgically instead of ingesting full documents.
Key Insight: The directory hierarchy was the coordination mechanism. When each agent knows where to look and where to write, explicit coordination overhead drops to near zero.
VII. Common Pitfalls
❌ File Dumping: Creating files without structure → ✅ Use directory hierarchy
❌ Orphan Documents: No links to/from other content → ✅ Always link related content
❌ Stale Content: Old drafts never finalized or archived → ✅ Weekly review and cleanup
❌ Vague Naming: "thoughts.md", "notes.md" → ✅ Descriptive names with dates
❌ No Metadata: Can't filter or discover → ✅ Always include frontmatter
VIII. Related Skills
handoff-protocol — Use for creating structured handoffs between agents in the workspace
decision-propagation — Use for documenting and propagating decisions across workspace documents
agent-teaching — Use for creating teaching artifacts that other agents can learn from
compression-ritual — Compress workspace session context into memory artifacts
status-writing — Maintain workspace-level status documents for project health visibility
IX. Skill Metadata
Token Savings: ~10,000-20,000 tokens per session (surgical reading, structured navigation, metadata filtering)
Quality Impact: Ensures workspace remains organized, discoverable, and collaborative
Maintenance: Update when workspace structure evolves
Related Skills:
handoff-protocol — Use for creating structured handoffs in workspace
decision-propagation — Use for documenting and propagating decisions
agent-teaching — Use for creating teaching artifacts in workspace
Last Updated: 2026-04-06
Maintained By: Tres Pies Design
Status: Active