skill-context-detection
Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
Skill by mhdxbilal
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/mhdxbilal-skill-context-detection
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About
Use cases: productivity
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/skill-context-detection
What's inside
- Skill name
skill-context-detection- Description
- Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
- License
- MIT
- Instructions
- 270 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Context Detection - Internal Skill
## Purpose
This skill provides **automatic context detection** to determine whether the user is working in a **Development context** (code-focused) or **Knowledge context** (research/strategy-focused). This replaces the manual `/octo:km` toggle with intelligent auto-detection.
## Detection Algorithm
When a workflow skill activates, detect context using these signals:
### Step 1: Check for Explicit Override
If user has explicitly set mode via `/octo:km on` or `/octo:km off`, respect that setting.
```bash
# Check if knowledge mode is explicitly set
if [[ -f ~/.claude-octopus/config/knowledge-mode ]]; then
EXPLICIT_MODE=$(cat ~/.claude-octopus/config/knowledge-mode)
if [[ "$EXPLICIT_MODE" == "on" ]]; then
echo "knowledge"
exit 0
elif [[ "$EXPLICIT_MODE" == "off" ]]; then
echo "dev"
exit 0
fi
fi
# If "auto" or not set, proceed with auto-detection
```
### Step 2: Analyze Prompt Content (Strongest Signal)
**Knowledge Context Indicators** (check prompt for these terms):
- Business/strategy: "market", "ROI", "stakeholders", "strategy", "business case", "competitive"
- Research: "literature", "synthesis", "academic", "papers", "research question"
- UX: "personas", "user research", "journey map", "pain points", "interviews"
- Deliverables: "presentation", "report", "PRD", "proposal", "executive summary"
**Dev Context Indicators** (check prompt for these terms):
- Technical: "API", "endpoint", "database", "function", "class", "module"
- Actions: "implement", "debug", "refactor", "test", "deploy", "build"
- Artifacts: "code", "tests", "migration", "schema", "controller"
**Scoring:**
- Count knowledge indicators in prompt
- Count dev indicators in prompt
- Higher count wins
- If tied, check project context (Step 3)
### Step 3: Analyze Project Context (Secondary Signal)
**Dev Project Indicators:**
- Has `package.json`, `Cargo.toml`, `go.mod`, `pyproject.toml`, `pom.xml`
- Has `src/`, `lib/`, `app/` directories with code files
- Recent files are `.ts`, `.js`, `.py`, `.go`, `.rs`, `.java`
**Knowledge Project Indicators:**
- Has `docs/`, `research/`, `strategy/`, `reports/` directories
- Majority of files are `.md`, `.docx`, `.pdf`, `.pptx`
- No code package managers detected
### Step 4: Default Fallback
If signals are ambiguous or equal:
- In a git repo with code files → Default to **Dev Context**
- No code files detected → Default to **Knowledge Context**
---
## Context Output Format
Return detected context as a structured object for use by workflow skills:
```json
{
"context": "dev" | "knowledge",
"confidence": "high" | "medium" | "low",
"signals": {
"prompt_indicators": ["API", "endpoint", "database"],
"project_type": "node_typescript",
"explicit_override": false
}
}
```
---
## How Workflow Skills Use Context
### flow-discover (Research)
| Aspect | Dev Context | Knowledge Context |
|--------|-------------|-------------------|
| **Research Focus** | Technical implementation, library comparison, code patterns | Market analysis, academic synthesis, competitive research |
| **Primary Agents** | Codex (implementation), Gemini (ecosystem) | Gemini (analysis), research-synthesizer |
| **Output Format** | Code examples, API comparisons, tech recommendations | Reports, frameworks, strategic recommendations |
| **Visual Banner** | `🔍 [Dev] Discover Phase: Technical research` | `🔍 [Knowledge] Discover Phase: Strategic research` |
### flow-develop (Build)
| Aspect | Dev Context | Knowledge Context |
|--------|-------------|-------------------|
| **Build Focus** | Code generation, implementation, architecture | PRDs, strategy docs, presentations |
| **Primary Agents** | Codex (code), backend-architect, tdd-orchestrator | product-writer, strategy-analyst, exec-communicator |
| **Output Format** | Source files, tests, migrations | Documents, frameworks, action plans |
| **Visual Banner** | `🛠️ [Dev] Develop Phase: Building code` | `🛠️ [Knowledge] Develop Phase: Building deliverables` |
### flow-deliver (Review)
| Aspect | Dev Context | Knowledge Context |
|--------|-------------|-------------------|
| **Review Focus** | Code quality, security, performance | Document quality, argument strength, completeness |
| **Primary Agents** | code-reviewer, security-auditor | exec-communicator, strategy-analyst |
| **Quality Gates** | OWASP, test coverage, maintainability | Evidence quality, clarity, actionability |
| **Visual Banner** | `✅ [Dev] Deliver Phase: Code review` | `✅ [Knowledge] Deliver Phase: Document review` |
---
## Visual Indicator UpdateFrom mhdxbilal/Ai, MIT.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 1
- Last commit (this folder)
- May 19, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/mhdxbilal/Ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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skill-context-detection. Agent Mart. https://agentmart.dev/skills/mhdxbilal-skill-context-detection (last updated 2026-10-24)