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chacharin

mcp-lightrag

by chacharin

delete_documents

Permanently delete documents and all associated data (text chunks, vector embeddings, graph relations). This irreversible action runs in the background; confirm completion via document status or listing.

Instructions

DESTRUCTIVE: permanently deletes documents and all their associated data (status, text chunks, vector embeddings, related graph data). This cannot be undone. Runs in the background; use get_track_status or list_documents afterward to confirm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idsYesIDs of the documents to delete.
delete_fileNoAlso delete the corresponding file from the upload directory.
delete_llm_cacheNoAlso delete cached LLM extraction results for these documents.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden. It explicitly discloses destructive nature ('DESTRUCTIVE', 'permanently deletes'), irreversibility ('cannot be undone'), and async behavior ('runs in the background'), plus associated data deletion. This exceeds typical expectations and fully covers 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.

Conciseness5/5

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

The description is three sentences, front-loaded with 'DESTRUCTIVE' to immediately signal risk. Every sentence adds value: destructive scope, irreversibility, and async confirmation steps. No wasted words.

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 tool has an output schema (as indicated) and no annotations, the description covers essential behavioral context: destructive nature, async execution, and post-verification steps. It does not omit critical details an agent needs to use it correctly, such as permanent deletion and confirmation mechanism.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all parameters (doc_ids, delete_file, delete_llm_cache). The description does not add parameter-specific detail beyond the schema, so a baseline of 3 is appropriate. It does not introduce ambiguity or missing semantics.

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 states a specific verb ('deletes') and resource ('documents'), and clarifies scope ('permanently deletes documents and all their associated data'). It distinguishes from siblings like delete_entity and clear_all_documents by specifying it targets documents and their related data.

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

Usage Guidelines3/5

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

The description provides clear post-usage guidance ('use get_track_status or list_documents afterward to confirm') but does not explicitly contrast with alternative deletion tools (e.g., clear_all_documents). While context is clear, it lacks explicit when-not-to-use guidance relative to siblings.

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