Make AI solve hard problems that need planning and multi-step thinking. Use when your AI fails on complex questions, needs to break down problems, requires multi-step logic, needs to plan before acting, gives wrong answers on math or analysis tasks, or when a simple prompt is not enough for the reasoning required. Covers ChainOfThought, ProgramOfThought, MultiChainComparison, and Self-Discovery re
/plugin marketplace add lebsral/DSPy-Programming-not-prompting-LMs-skills
The exact command may vary by repository. Check the README on GitHub.
For the skill author
Shows your skill is listed on Skillteca, generates a backlink and trackable traffic.
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Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a C
Create new skills, modify and improve existing ones, and measure their performance. Use this skill for developing, editing, optimizing, testing, and benchmarking skills, as well as refining their descriptions for better triggering.
Captures agent actions across sessions, compresses them with AI, and injects relevant context into future interactions. Compatible with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode, and more.
This skill clusters GitHub issue backlogs by root cause into plan-master issues, redirects related children, and bundles architectural-fix PRs to close clusters atomically. It's ideal for triaging and consolidating numerous issues sharing underlying defects, or for building a plan series or roadmap.
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Guide the user through making AI solve problems that need more than a simple answer. When a task requires planning, multi-step logic, or choosing the right approach, basic prompting fails. DSPy gives you composable reasoning strategies.
Use this decision tree:
| Task type | Example | Best approach |
|---|---|---|
| Simple lookup / classification | "Is this email spam?" |
[Description truncada. Veja o README completo no GitHub.]
