Claude Prompt Engineering

Knowledge snapshot from: 2026-02-20

Generated by: cogworks

Overview

When to Use This Skill

• Design or review Claude system prompts
• Tune adaptive or extended thinking behavior
• Improve tool orchestration and parallelization
• Handle long-horizon or multi-window workflows
• Add prompt-injection and data-leakage safeguards
• Reduce verbosity while preserving answer quality

Quick Decision Cheatsheet

• Opus 4.6: Use adaptive thinking (

  low|medium|high|max

  ) only when task complexity justifies it.
• Sonnet 4.5: Use extended thinking for legacy workflows; minimum budget 1024 tokens.
• Simple tasks: Prefer no explicit thinking config.
• Long tasks: Persist state in files + git checkpoints.
• Independent reads/searches: Run tool calls in parallel.
• Risky/irreversible actions: Ask for confirmation first.
• Production exposure: Apply defense-in-depth (input, architecture, output).

Supporting Docs

• reference.md

  : Canonical guidance, decision rules, anti-patterns, and sources

• patterns.md

  : Reusable patterns and templates

• examples.md

  : Compact before/after prompt examples

Model Routing Contract

• primary-capability-class: reasoning
• fallback-capability-class: workhorse
• task-to-capability mapping:
  • source ingestion/extraction: workhorse
  • synthesis/contradiction resolution: reasoning
  • final skill drafting: workhorse
• quality gates tied to capability:
  • reasoning: resolve contradictions and justify the interpretation
  • workhorse: complete structure with citations and no stubs
• runtime model resolution:
  • map capability classes to provider/runtime defaults automatically
  • never ask the user to choose a model

Invocation

/claude-prompt-engineering