AgentSkillsCN

cursor

将任务需求转化为 Cursor CLI 命令。由 cursor-driver 代理调用,通过 Cursor 执行编码任务。

SKILL.md
--- frontmatter
name: cursor
description: Translates task requirements into Cursor CLI commands. Used by cursor-driver agent to execute coding tasks via Cursor.

Cursor CLI Skill Guide

Baseline Rules

Always apply these for programmatic (headless) execution:

  • -p "<prompt>" — required for headless mode
  • --output-format text — recommended for clean output capture

Command Templates

New Task (analysis/read-only)

bash
agent -p "<prompt>" --mode ask --output-format text

New Task (with file edits)

bash
agent -p "<prompt>" --mode agent --output-format text

New Task (planning only)

bash
agent -p "<prompt>" --mode plan --output-format text

With model selection

bash
agent -p "<prompt>" --model gpt-5 --output-format text

Resume Session (latest)

bash
agent resume -p "<prompt>" --output-format text

Resume Session (specific)

bash
agent --resume="<chat-id>" -p "<prompt>" --output-format text

List Previous Sessions

bash
agent ls

Execution Modes

Task TypeFlagNotes
Analysis, review, Q&A--mode askRead-only, no file changes
Create or edit files--mode agentFull agent capabilities
Planning, architecture--mode planGenerates plan without execution

Model Selection

When the calling agent specifies requirements, translate to flags:

RequirementFlagNotes
Default / high-quality--model gpt-5Best for complex reasoning
Fast / cheap--model gpt-4oQuick, straightforward tasks
Claude--model claude-sonnetAnthropic model option

If not specified, use default model (no flag needed).

Output Formats

FormatFlagUse Case
Text--output-format textProgrammatic processing, CI/automation
Default(none)Interactive/human-readable output

Cloud Agent Handoff

For complex tasks requiring cloud processing, prefix the prompt with &:

bash
agent "& refactor the auth module and add comprehensive tests"

Interpreting Results

Success indicators

  • Clean text output with expected content
  • Exit code 0
  • Response addresses the original request

Failure indicators

  • Non-zero exit code
  • Error messages in output
  • Missing expected deliverables

Scope creep indicators

  • Mentions of "I also..." or "While I was at it..."
  • Changes to files not mentioned in the original request
  • Response describes work beyond the original request

Redirection indicators

  • Output describes different work than requested
  • "Instead of X, I did Y..."
  • Solving a different problem than specified

After Completion

Report to user: "You can resume this Cursor session by saying 'cursor resume'."

Session Management

  • agent ls — List all previous conversations
  • agent resume — Resume most recent session
  • agent --resume="<id>" — Resume specific session by ID

Error Handling

  • If command exits non-zero: stop and report the error
  • If output contains error messages: summarize and report
  • If output contains warnings: summarize and ask how to proceed

Reference

Useful Patterns

bash
# Code review (read-only)
agent -p "Review src/auth.py for security issues" --mode ask --output-format text

# Implement feature
agent -p "Add input validation to the login form" --mode agent --output-format text

# Generate plan
agent -p "Plan the migration from REST to GraphQL" --mode plan --output-format text

# Continue previous work
agent resume -p "Now add unit tests for the changes"

# Cloud-powered complex task
agent "& analyze codebase architecture and suggest improvements"

Interactive Mode

For complex multi-step tasks, you may run agent without -p to enter interactive mode:

bash
agent

Then provide prompts conversationally. Use this when:

  • The task requires back-and-forth dialogue
  • You need to inspect intermediate results before continuing
  • The task scope may evolve based on findings