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agent-reproduce-feature

QwenLM · Данни и AI

Use when reproducing an existing Codex or Claude Code feature in Qwen Code or another agent CLI by choosing a reference agent, capturing HTTP request bodies, prompts, tool/function schemas, terminal output, and then implementing the matching behavior in the target repo.

Оригинален текст · няма потвърден превод на български

Теми: agentic · ai · ai-agent · ai-coding · cli · coding-agent · developer-tools · llm · mcp · qwen · terminal · typescript

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Apache-2.0
Последна проверка на записа
20.09.2026 г.

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Agent Reproduce Feature

Purpose

Use this skill to turn an observed feature from a reference agent into an implementation task for Qwen Code. The workflow treats the current session as the outer harness and runs a nested reference agent process as the program under test.

Default target repo: the current working directory. Use a user-specified path only when the user explicitly provides one.

Reference Agent Selection

Start by selecting exactly one reference agent:

  • codex: use nested Codex as the reference implementation.
  • claude-code: use nested Claude Code as the reference implementation.

If the user did not choose one, ask once before capture. Then discover the local commands instead of assuming them:

command -v codex || true
command -v claude || command -v claude-code || true

Record the selected adapter in the run notes or scenario:

{
  "reference_agent": "codex",
  "reference_interactive_command": "codex",
  "reference_headless_command": "codex exec",
  "target_agent": "qwen-code",
  "target_repo": "."
}

Workflow

  1. Define the feature surface in one sentence: command, trigger, expected UI/output, and a minimal prompt that exercises it.
  2. Select codex or claude-code as the reference agent and discover its local launch command.
  3. Inspect the target repo enough to identify the likely module boundaries and Qwen Code launch command before changing code.
  4. Run the nested reference agent against the feature with capture enabled:
    • Local state capture via scripts/capture_state.py before and after the scenario.
    • HTTP/body capture via scripts/run_with_mitm.sh.
    • Terminal capture via scripts/run_tmux_capture.sh when the feature is interactive or TUI-visible.
    • Headless/non-interactive execution when the feature has a stable command-line path.
  5. Extract behavioral facts from the trace:
    • system/developer prompt deltas relevant to the feature
    • request body shape, including messages, tools, functions, schemas, tool choice, model settings
    • visible terminal states and command output
    • local agent state changes, file edits, exit status, and error paths
  6. Implement the smallest compatible behavior in Qwen Code using its existing patterns.
  7. Add focused tests or a reproducible smoke command.
  8. Hand off to $agent-reproduce-align when implementation exists and parity needs iteration.

Целият SKILL.md в GitHub