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epsilongraph

epsilongraph

by silverenternal
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Python
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vault_load_bearing

Rank notes by how much of an Obsidian vault a change would falsify, revealing which few notes are load-bearing so you know where to be careful.

Instructions

Every note ranked by how much of the vault a change to it would falsify. On this vault the answer is bimodal: a handful of notes falsify 30-50% of the corpus and the large majority falsify nothing. Use this to decide where to be careful.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "vault_load_bearing"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
semanticsNofalsified

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the character of the result (bimodal: a few notes at 30-50% falsification, most at none) and the semantics of the ranking, which is real behavioral value. It says nothing about truncation via limit, cost, or what the returned records look like.

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?

Three short sentences, front-loaded with what the tool returns. The middle sentence is domain flavor but it does convey the actual distribution an agent will see, so it earns most of its space.

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

Completeness2/5

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

No annotations, no output schema, and two undocumented parameters with zero schema coverage. The description covers the ranking concept but not what a call actually returns or how limit/semantics shape it, leaving the agent under-informed for a tool with this much structured ambiguity.

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

Parameters2/5

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

Schema coverage is 0% and neither parameter is explained. The description only implies the default "falsified" semantics; the "needs_reread" enum value and the limit/pagination behavior are left entirely undocumented, so it fails to compensate for the coverage gap.

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 first sentence states a specific operation: rank every note by how much of the vault a change to it would falsify. That is a clear verb+resource, well beyond a tautology. It does not, however, differentiate itself from the sibling vault_impact, which sounds like it could compute a similar thing.

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?

"Use this to decide where to be careful" gives an intended purpose, but there is no when-not guidance, no prerequisites, and no routing against the ten sibling tools (notably vault_impact). Usage is implied rather than specified.

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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