AgentSkillsCN

advanced-tool-usage

多阶段工具编排指南，以及使用“redirect_tool_call”处理大数据的技巧。当您需要在不耗尽上下文窗口的情况下处理大量数据，或构建复杂的数据管道时，可使用此功能。

SKILL.md
--- frontmatter
name: advanced-tool-usage
description: Guidelines for multi-stage tool orchestration and handling large data using 'redirect_tool_call'. Use this when you need to process large amounts of data without exhausting the context window or when building complex data pipelines.

Advanced Tool Usage

Core Principles

  • •Context Economy: Never bring raw, voluminous data into the conversation if you only need a refined subset.
  • •Pipeline Thinking: View tools as modular blocks that can pass data through files.
  • •Offloading: Use redirect_tool_call to "capture" output into external storage.

Patterns

1. The Pipelining Pattern

When a tool's output is the input for another tool:

  1. •Redirect: Call the first tool using redirect_tool_call.
  2. •Process: Call the second tool (e.g., python_execute or shell_execute) and pass the file path created in step 1 as an argument.
  3. •Refine: Read only the final processed result into the conversation.

2. The Context Buffer Pattern

When working with large files or long logs:

  • •Redirect the reading tool (e.g., cat, tavily_search) to a temporary file.
  • •Use rg or grep to extract only the relevant lines from that file.

3. Workspace Management for Pipelines

When building multi-stage pipelines that generate multiple files:

  • •Use shell_execute with mktemp -d to create a dedicated scratch directory.
  • •Direct all intermediate redirect_tool_call outputs into that directory to keep the workspace clean.
  • •Example: redirect_tool_call(..., output_file="/tmp/tmp.X/step1.json")

4. The Large Data Export

When the user requests a result that is too large for markdown (e.g., a 5MB JSON dump):

  • •Use redirect_tool_call with a specific output_file name.
  • •Inform the user of the file location instead of printing the content.

When to use redirect_tool_call

  • •The expected output is > 50 lines and the tool does NOT support its own redirection (e.g., searches, API calls).
  • •The output is raw data (JSON, CSV) that needs further processing by another tool.
  • •You are chaining an MCP tool into a local processing tool.

Note: For shell_execute or python_execute, always use internal file writing (> or file.write()) instead of redirect_tool_call for maximum efficiency.

References