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load_document

Parse a Markdown file into heading-bounded chunks, embed and index them for semantic search, replacing prior chunks for the same path so AI agents can retrieve relevant sections.

Instructions

Parse a markdown file into heading-bounded chunks, embed each chunk, and index them for semantic search. Replaces existing chunks for the same path on reload. Requires [embeddings] in config.toml.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute or repo-relative path to the markdown file.
projectNoOptional project tag. Chunks tagged with a project can be bulk-deleted via delete_project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does meaningful work: it discloses upsert semantics ("Replaces existing chunks for the same path on reload") and an environment prerequisite. It stops short of authority requirements, failure behavior, or return shape, but the mutation profile is well conveyed.

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?

Three short sentences, each earning its place: operation, replacement behavior, and prerequisite. The core action is front-loaded with zero filler.

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

Completeness4/5

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

For a two-parameter tool with no output schema and no annotations, the description covers the action, the idempotency/replacement semantics, and the config requirement well. Minor gaps remain around permissions and failure modes, but nothing critical for correct invocation is missing.

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 coverage is 100%, so both parameters are already fully documented in the schema, including the delete_project tie-in. The description adds no syntax, format, or constraint detail beyond that, so the baseline 3 applies.

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

Purpose4/5

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

The description gives a precise verb chain (parse, embed, index) and a clear resource (markdown file), specifically describing the indexing operation. It is functionally distinct from siblings like query_document and clear_document, but it never names them, so the differentiation must be inferred.

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?

It states a real prerequisite ("Requires [embeddings] in config.toml") and implies the reload/upsert use case, which is useful guidance. However, it gives no explicit when-to-use vs. when-not, and never routes the agent to query_document, clear_document, or delete_project.

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