🧠
AI EngineeringShell

Context Detection

by nyldn

Context Detection is an AI Engineering skill for Claude Code, published by nyldn in claude-octopus.

4K stars374 forkson nyldn/claude-octopusAdded 2026/08/16Repository updated 2026/08/16
ai-agentsai-orchestrationclaude-codeclaude-code-plugincodexcopilotdeveloper-toolsdouble-diamondgeminimulti-aimulti-llmollama
Install in seconds
Install Context Detection
Copy Context Detection into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/nyldn/claude-octopus/tree/main/skills/skill-context-detection ~/.claude/skills/skill-context-detection

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/nyldn/claude-octopus.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
skills/skill-context-detection/SKILL.md in nyldn/claude-octopus
Installs to
~/.claude/skills/skill-context-detection
Collection
One of 25 skills cataloged from this repository
Category
AI Engineering2451 skills

What Context Detection does

Context Detection automatically identifies whether the current task is development or knowledge work, so agent workflows can tailor research, build, and review behavior. It checks explicit overrides, prompt indicators, and project structure before returning a confidence-scored context.

Context Detection is cataloged under AI Engineering on DirSkills. Context Detection comes from a repository tagged ai-agents, ai-orchestration, claude-code, claude-code-plugin and codex.

Documentation

README

Host: Codex CLI — This skill was designed for Claude Code and adapted for Codex. Cross-reference commands use installed skill names in Codex rather than /octo:* slash commands. Use the active Codex shell and subagent tools. Do not claim a provider, model, or host subagent is available until the current session exposes it. For host tool equivalents, see skills/blocks/codex-host-adapter.md.

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.

This is the opening of the README. Read the full README on GitHub.

Commands Context Detection provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

  • /review
  • /security-review

Frequently asked about Context Detection

  • What else does nyldn publish alongside Context Detection?

    Context Detection is one of 25 skills that DirSkills catalogs from nyldn/claude-octopus, the repository it ships in. Its siblings there include AI Debate Hub, Agent Topology Audit and Code Review. Each one is a separate skill with its own page in this directory, installs the same way Context Detection does, and is maintained by nyldn in that same repository. The rest of the collection is listed on the nyldn/claude-octopus page.

  • How does Context Detection compare to other AI Engineering skills?

    Context Detection ranks #535 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Context Detection against them. Open each page to compare what they document and how they install.

More from nyldn/claude-octopus

Context Detection is one of 25 skills cataloged on DirSkills from nyldn/claude-octopus.

See all 25 skills
🐙
2w ago

AI Debate Hub

AI Debate Hub runs structured multi-provider AI debates with Claude and available advisors to help make critical decisions. Use it when you want multiple AI perspectives synthesized before choosing a technical or strategic direction.
AI Engineering
4K374
🕸️
2w ago

Agent Topology Audit

Agent Topology Audit evaluates whether a multi-agent setup earns its coordination cost. Use it before adding an agent or when a workflow feels slow or agents agree without adding signal.
AI Engineering
4K374
🐙
2w ago

Code Review

Code Review runs a multi-LLM pipeline to analyze pull requests for security vulnerabilities, code quality, performance, TDD compliance, and stubs. Use it before merging changes with security or architecture impact.
Quality
4K374
🔍
2w ago

Content Pipeline

Content Pipeline extracts patterns and anatomy from up to five URLs so you can reverse-engineer content strategies. Use it to analyze articles, X threads, newsletters, YouTube descriptions, or LinkedIn posts and generate a structural blueprint, psychological playbook, and interview questions for recreating similar content.
Writing
4K374
🟢
2w ago

Copilot Provider

Copilot Provider integrates GitHub Copilot CLI as an optional zero-cost provider in the Claude Octopus multi-LLM ecosystem, using programmatic mode for research and exploration. Use it to supplement other providers with Copilot responses, with graceful degradation if unavailable.
AI Engineering
4K374
💰
2w ago

Cost Projections

Cost Projections estimates remaining workflow costs from per-phase averages and warns when projections exceed a budget ceiling. Use it when you need to track and forecast spend across multi-step AI workflows.
AI Engineering
4K374