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Kilonova MCP

Kilonova MCP

by MilnaOS
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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dot_load

Load a topic's full Document of Truth to restore persistent working memory and project context at session start.

Instructions

Load the full DOT (Document of Truth) for a KB topic. A DOT is a compressed, structured reference document with a TOC and cards. Use dot_load("claude_context") at session start to load your persistent working memory.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "<topic>"
    },
    "name": "dot_load"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicYesKB topic (e.g. "claude_context")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations, so the description carries the burden. It discloses the payload shape (TOC and cards) and the persistence role of the document, which implies a read-only operation. It does not state whether loading is side-effect free, whether it creates the topic if missing, or how large the response can get.

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, front-loaded with the action, followed by a definition the agent needs, followed by the operative usage rule. No 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 one-parameter read tool with no output schema, the description covers what the tool does, what comes back (TOC plus cards), and when to call it. What is missing is only the relationship to sibling loaders, which for this simple tool is a minor gap.

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% with a single documented 'topic' parameter, so the baseline is 3. The description reinforces the parameter by showing a concrete value in the example call, but adds no format, casing, or validation rules beyond the schema.

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?

A specific verb ('Load') and resource (the full DOT for a KB topic), plus an inline definition of what a DOT is. It does not distinguish itself from the sibling kb_load, so an agent must infer the difference between loading a DOT and loading a KB.

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

Usage Guidelines4/5

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

Gives a concrete trigger: 'Use dot_load("claude_context") at session start to load your persistent working memory.' That is clear when-to-use guidance with a literal example call. It omits when-not-to-use and does not name kb_load/kb_topics as alternatives.

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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