obsidian-local-mcp

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Impact Of

impact_of

Analyze the impact of a single code node: see what it must read, what depends on it, which tests exercise it, what documentation covers it, and any danger flags.

Instructions

Impact analysis for one specific node: what it needs (MUST_READ), what depends on it (MAY_CHANGE), what exercises it (MUST_TEST), the knowledge that documents it, and anything flagged DANGER.

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": {
      "id": "<id>"
    },
    "name": "impact_of"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes
`vault`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 11, 2026

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, yet it never states that the operation is read-only, how deep or expensive the traversal is, or whether a vault/permission scope is required. It does add real value by naming the semantic categories returned (needs vs. depends-on vs. exercises vs. DANGER), which goes beyond raw structure, but behavioral traits like cost and safety are unstated.

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?

A single front-loaded sentence stating purpose first, then the payload categories. Every clause earns its place and there is no filler or repetition.

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

Completeness3/5

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

The presence of an output schema means return structure need not be explained, and the description usefully glosses the result labels. However, with 0% parameter coverage and no annotations, an agent still lacks the input-format details and cost/auth context needed to invoke this confidently, so it is only minimally complete.

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 description coverage is 0%, so the description must compensate for the two undocumented parameters and it does not. It never clarifies what form `id` takes (node ID? path? note?), nor what `vault` selects or how the null default is resolved.

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 specific function — impact analysis for a single node — and enumerates the distinct result categories (MUST_READ, MAY_CHANGE, MUST_TEST, documentation, DANGER), which makes it clearly separable from graph-walking siblings like neighbors or path_between. It stops short of naming those alternatives explicitly, so it is clear but not sibling-routing.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance, and no alternative tool is named. The reader must infer the use case (e.g. assessing blast radius before a change) purely from the list of returned categories, leaving no explicit context or exclusions.

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