Knowledge Work Mode - Context Override Skill

Context Auto-Detection (v7.8+)

Claude Octopus now auto-detects work context! The system analyzes your prompt and project to determine whether you're in a Dev Context (code-focused) or Knowledge Context (research/strategy-focused).

You typically don't need this skill - context is detected automatically when you use:

• octo research X - Auto-detects dev vs knowledge research
• octo build X - Auto-detects code vs document building
• octo review X - Auto-detects code vs document review

When to Use This Override

Use ONLY when auto-detection is wrong:

• Auto-detection chose Dev but you want Knowledge behavior
• Auto-detection chose Knowledge but you want Dev behavior
• You want to force a specific context for the entire session

Override Commands

Force Knowledge Context

bash
/octo:km on

All subsequent workflows will use Knowledge Context until reset.

Force Dev Context

bash
/octo:km off

All subsequent workflows will use Dev Context until reset.

Return to Auto-Detection

bash
/octo:km auto

Context detection returns to automatic mode.

Check Current Status

bash
/octo:km

Shows current mode (auto, knowledge, or dev).

How Auto-Detection Works

When you use any octo workflow, context is detected by analyzing:

1. Prompt Content (strongest signal):

• Knowledge indicators: "market", "ROI", "stakeholders", "strategy", "personas", "presentation", "report", "PRD"
• Dev indicators: "API", "endpoint", "database", "implementation", "code", "function", "deploy"

1. Project Type (secondary signal):

• Has package.json, Cargo.toml, go.mod → Dev Context
• Mostly .md, .docx, .pdf files → Knowledge Context

1. Explicit Override (if set via /octo:km):

• Overrides all auto-detection until reset to "auto"

Visual Indicator Shows Context

When workflows run, you'll see the detected context in the banner:

Dev Context:

🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-provider research mode
🔍 [Dev] Discover Phase: Technical research on caching patterns

Knowledge Context:

🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-provider research mode
🔍 [Knowledge] Discover Phase: Market analysis for APAC expansion

Examples of Auto-Detection in Action

Example 1: Technical Research (Auto → Dev)

User: "octo research caching strategies for our Node.js API"

Claude: (auto-detects Dev Context from "Node.js API")

🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-provider research mode
🔍 [Dev] Discover Phase: Technical research on caching strategies

[Researches with technical/implementation focus]

Example 2: Market Research (Auto → Knowledge)

User: "octo research market opportunities in healthcare AI"

Claude: (auto-detects Knowledge Context from "market opportunities")

🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-provider research mode
🔍 [Knowledge] Discover Phase: Strategic research on healthcare AI market

[Researches with business/strategic focus]

Example 3: Override When Auto Gets It Wrong

User: "octo research React patterns" Claude: (auto-detects Dev) 🔍 [Dev] Discover Phase...

User: "Actually, this is for a presentation. Force knowledge mode."

Claude: "Setting context override to Knowledge Mode."

bash
/octo:km on

User: "octo research React patterns" Claude: (uses override) 🔍 [Knowledge] Discover Phase... (focuses on trends, adoption, strategic implications)

Example 4: Check Current Status

User: "What context mode am I in?"

Claude:

Current mode: Auto-detection (no override set)
Last detected context: Dev (based on project having package.json)

To override: /octo:km on (force Knowledge) or /octo:km off (force Dev)
To return to auto: /octo:km auto

What Changes Per Context

Dev Context 🔧

| Workflow | Focus | |----------|-------| | octo research X | Technical implementation, libraries, code patterns | | octo build X | Code generation, architecture, tests | | octo review X | Code quality, security, performance | | Agents | codex, backend-architect, code-reviewer, security-auditor |

Knowledge Context 🎓

| Workflow | Focus | |----------|-------| | octo research X | Market analysis, competitive research, literature synthesis | | octo build X | PRDs, strategy docs, presentations, reports | | octo review X | Document quality, argument strength, completeness | | Agents | strategy-analyst, ux-researcher, exec-communicator, product-writer |

Document Delivery 📄

After running knowledge workflows, export to professional formats:

• DOCX - Word documents for reports, business cases
• PPTX - PowerPoint presentations for stakeholder decks
• XLSX - Excel spreadsheets for data analysis

Just say: "Export this to Word" or "Create a PowerPoint presentation"

Override Command Reference

| Command | Description | |---------|-------------| | /octo:km | Show current status (auto, on, or off) | | /octo:km on | Force Knowledge Context for all workflows | | /octo:km off | Force Dev Context for all workflows | | /octo:km auto | Return to auto-detection (default) |

When NOT to Use Override

Don't override if:

• Auto-detection is working correctly
• You're doing mixed work (let each prompt be detected individually)
• You just want to see what context was detected (check the banner)

Override is for:

• Forcing a specific context for an entire session
• Correcting persistent misdetection
• Specific use cases where you know better than auto-detect

Cross-Task Learnings

At the end of significant work sessions, extract learnings:

1. What task type was this? (debugging, implementation, research, review)
2. What approach worked? What failed?
3. What would you do differently next time?

Store learnings in .claude-octopus/learnings/<date>-<summary>.json:

json
{
  "date": "2026-03-21",
  "task_type": "debugging",
  "approach": "Traced the error from the test failure back to the API handler",
  "outcome": "success",
  "lesson": "Always check middleware ordering before investigating handler logic"
}

Each learning file captures: task_type, approach, outcome, and lesson.

Session Start: Relevance Matching

At session start, check for relevant learnings:

• Read .claude-octopus/learnings/ directory
• Match by task type and file patterns relevant to the current work
• Inject top 3 most relevant learnings as context (within ~5% token budget)
• Prefer recent learnings; deprioritize those older than 30 days

Budget Controls

• Maximum 5 learnings extracted per session (prevents runaway writes)
• Maximum 50 learning files retained (oldest pruned automatically)
• Relevance injection capped at 3 learnings and ~5% of available token budget
• Learning files are lightweight JSON (~200 bytes each)

Related Skills

• /octo:discover - Research workflow (auto-detects context)
• /octo:develop - Build workflow (auto-detects context)
• /octo:deliver - Review workflow (auto-detects context)
• /octo:docs - Document export (works in both contexts)