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export_claude_md

Export learned behavioral rules as a Markdown bullet list for manual inclusion in CLAUDE.md. Reads promoted rule-level patterns and produces compact Markdown without modifying files.

Instructions

Render rule-level patterns as Markdown ready to paste into CLAUDE.md.

    Use this when a Claude client needs a compact Markdown block of learned
    rules to include manually in CLAUDE.md. It reads promoted rule-level
    patterns only; no files are modified.

    Produces one bullet per rule with pattern key, category tag, confidence
    count, and explain text. The output is a freestanding Markdown section;
    no surrounding headers or context are added.

    For idempotent in-place injection into an existing CLAUDE.md (preserving
    other content via marker tags), use inject_claude_md() instead.
    For multi-platform output (Cursor, Windsurf, Codex), use
    export_platform() instead.

    Returns:
        Dict with keys: "markdown" (str — the rendered block; empty
        string if no rules exist), "rule_count" (int).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes read-only operation, output structure (bullet per rule with key, category, confidence count, explain text), and return type. No annotations exist, so description fully carries behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with purpose, usage, and output sections. Slightly verbose in middle paragraph, but front-loaded and clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete for a zero-parameter tool: covers purpose, usage, output format, return type, and alternatives. No missing context given simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters, so baseline is 4. Description does not add parameter info, but none is needed. Focus on output is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it renders rule-level patterns into Markdown for CLAUDE.md, specifying verb, resource, and output format. Distinguishes from siblings like inject_claude_md and export_platform.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use (when a compact Markdown block is needed for manual inclusion) and what it does not do (no file modification, only promoted rules). Provides alternatives for idempotent injection and multi-platform export.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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