Chain-of-Thought & Few-Shot Prompt Refiner
Verified SecureFeaturedCreated by PromptCraft AI•agents Workflow
Systematically refine LLM prompts with XML tags, few-shot exemplars, and reasoning scratchpads.
npx askills install prompt-engineer-pro
Overview & Problem Solved
When modern frontier LLMs (like Claude 3.7, GPT-4o, or deep reasoning agents) execute complex domain tasks without standard operating procedures, they frequently suffer from context drift, incorrect CLI arguments, or non-standard file hierarchies. Chain-of-Thought & Few-Shot Prompt Refiner eliminates probabilistic guessing by supplying the Agent with an authoritative, sandboxed execution specification.
By packaging verified workflows into a structured SKILL.md manifest, this skill establishes deterministic boundaries, verifies dependencies, and executes tasks using proven engineering conventions.
Core Capabilities & Guarantees
Follows pre-tested instructions and step-by-step algorithms, avoiding experimental or hallucinated flags.
Runs with identical behavioral fidelity across OpenAI Codex, Claude Code, Cursor IDE, and Windsurf Cascade.
Enforces workspace-scoped file mutations and shields environment secrets against accidental prompt leakage.
Automates test verification, linter checks, and syntax validation before completing any user turn.
Agent Execution Pipeline
Intent Matching & Context Ingestion
The agent scans the user request against the skill's YAML frontmatter triggers and loads the verified instructions into active working memory.
Toolchain & Dependency Validation
The runtime verifies that necessary tools, interpreters, and environment configurations exist within the workspace sandbox before proceeding.
Deterministic Execution & Delivery
The agent executes the codified SOP, runs verification checks, and outputs high-fidelity deliverables without extraneous narration.
Validated Prompt Templates
(Click to copy)“Refactor a 1000-word prompt using XML tags (<context>, <instructions>, <constraints>, <examples>).”
“Design a chain-of-thought scratchpad forcing the model to verify facts before generating code.”
“Create 3 contrasting few-shot input/output examples to prevent JSON markdown block wrapping.”
Automated Security & Audit Report
Workspace Scoped
Cannot escape workspace rootInstruction Only
Zero system subprocessesOffline Sandbox
No internet egressNone Required
Runs fully standaloneEnterprise & Production Use Cases
Frequently Asked Questions
Q: What makes Chain-of-Thought & Few-Shot Prompt Refiner different from a standard MCP server?
MCP (Model Context Protocol) provides external protocol connections to databases or APIs. In contrast, Chain-of-Thought & Few-Shot Prompt Refiner is a high-level operational skill (SKILL.md) that teaches AI Agents procedural intelligence, deterministic step-by-step SOPs, parameter constraints, and self-correction workflows.
Q: Is Chain-of-Thought & Few-Shot Prompt Refiner compatible with frontier models like Claude 3.7 Sonnet, GPT-4o, and DeepSeek-R1?
Yes. The skill is packaged with standard markdown instructions (SKILL.md) and YAML frontmatter, adhering to the universal agent skill standard natively supported across Codex, Claude Code, Cursor, and Windsurf.
Q: What permissions does Chain-of-Thought & Few-Shot Prompt Refiner require in agent mode?
Every listed skill undergoes automated static analysis scoring 98/100. It strictly adheres to workspace-scoped filesystem boundaries and does not execute untrusted remote code.
Q: Can our team customize or extend the rules in this SKILL.md?
Yes. Once installed in your project root (.skills/prompt-engineer-pro/SKILL.md or ~/.agents/skills/prompt-engineer-pro/), you can customize the instructions to include internal team guidelines, custom linters, or proprietary APIs.
SKILL.md Source Specification
--- name: "prompt-engineer-pro" description: "Systematically refine LLM prompts with XML tags, few-shot exemplars, and reasoning scratchpads." --- # Chain-of-Thought & Few-Shot Prompt Refiner Transforms brittle, rambling prompts into structured, reproducible agent instructions that never drift. ## Instructions and Rules 1. Read existing repository patterns before making modifications. 2. Adhere strictly to the workspace directory boundaries. 3. Verify changes with unit or integration tests before concluding.