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execute_cleanup

Apply approved cleanup actions from knowledge repo analysis: move files and create missing categories using git mv, returning results and a rollback command.

Instructions

Execute approved cleanup actions from analyze_knowledge_repo().

    Side effects: moves files within the knowledge repo using git mv
    (preserves git history) and creates missing category directories.
    NEVER deletes any file. Requires analyze_knowledge_repo() to have
    been called first in this session.

    Use "all" to execute every proposed action, or pass a comma-separated
    list of specific action IDs (e.g. "a1,a3") to cherry-pick.
    Call reindex() after cleanup to rebuild the search index.

    Args:
        actions: Comma-separated action IDs from the analysis report,
                 e.g. "a1,a2,a5", or "all" to execute everything
        project: Target project name (optional)

    Returns:
        Per-action results (directories created, files moved), any errors,
        and a rollback command to undo the moves if needed.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionsYes
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it moves files using git mv, creates directories, and explicitly states 'NEVER deletes any file'. It also mentions return values and a rollback command.

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

Conciseness5/5

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

The description is concise at ~150 words, well-structured with clear sections, and front-loaded with the primary purpose. Each sentence provides valuable information without redundancy.

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?

Given the simple parameter structure and presence of an output schema, the description covers prerequisites, side effects, usage patterns, and return values, making it fully informative.

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

Parameters5/5

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

Despite 0% schema description coverage, the description fully explains both parameters with examples and format: 'actions: Comma-separated action IDs... e.g. "a1,a2,a5" or "all"' and 'project: Target project name (optional)'. This adds significant meaning beyond the schema.

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?

The description clearly states the tool's purpose: 'Execute approved cleanup actions from analyze_knowledge_repo().' It specifies the verb (execute) and resource (cleanup actions), and distinguishes it from sibling tools like analyze_knowledge_repo.

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?

The description explicitly states prerequisites ('Requires analyze_knowledge_repo() to have been called first') and follow-up steps ('Call reindex() after cleanup'), providing clear context for when and how to use the tool.

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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