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Pseudogiant-xr

PseudoLife-MCP

Official

document_ingest

Destructive

Index a file into a separate reference bank so background docs are retrieved by cosine similarity, keeping them apart from conversational memory.

Instructions

Index a file into the reference bank — a separate store for background documents (papers, manuals, codebases) retrieved by pure cosine similarity, kept apart from conversational memory.

Returns: {source, chunks_stored, chunks_total}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesPath to a .txt / .md / .pdf file, resolved on the SERVER's filesystem — with the Docker daemon, a path visible inside the container (e.g. a mounted volume), not a host path.
sourceNoSource tag for the chunks; defaults to the filename.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.15.0
    • addedInput schema / properties / path / description
      Added value: +"Path to a .txt / .md / .pdf file, resolved on the SERVER's filesystem — with the Docker daemon, a path visible inside the container (e.g. a mounted volume), not a host path."
    • addedInput schema / properties / source / description
      Added value: +"Source tag for the chunks; defaults to the filename."
  2. First observedv0.11.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare the write/destructive/non-idempotent profile, so the description only needs to add context. It adds meaningful architectural detail (separate reference store, pure cosine-similarity retrieval) but says nothing about what ingestion overwrites or how repeated ingests behave, which matters for a destructiveHint=true tool.

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?

Short and front-loaded: the core action and store definition come first, then the return shape. The return-value sentence is slightly redundant given an output schema exists, but the description remains efficient.

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 ingest tool with full schema coverage and an output schema, the description covers purpose, storage model, and return shape. The only real gap is behavioral detail on the destructive/non-idempotent nature already hinted at in annotations.

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 both parameters (path, source) are already documented in the schema, including the server-filesystem caveat. The description adds no parameter-level meaning beyond that, making the baseline 3 appropriate.

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?

States a specific verb and resource ('Index a file into the reference bank') and scopes it to background documents, which separates it from the memory_* cluster. It doesn't explicitly name document_search as the retrieval counterpart, so it's clear but not fully sibling-differentiated.

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?

Usage is only implied: the examples (papers, manuals, codebases) and 'kept apart from conversational memory' suggest when this store applies, but there is no explicit when-to-use statement and no named alternative such as document_search or memory_store.

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