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get_blender_reference_outline

List section headings and line numbers from a Blender reference guide so agents can locate relevant sections without reading the full document.

Instructions

List only section headings and their line numbers from one guide. Low-context alternative to reading the full document.

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": {
      "name": "<name>"
    },
    "name": "get_blender_reference_outline"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesExact .md guide filename

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden, and it does add value by disclosing the return shape (headings plus line numbers) even though no output schema exists. It omits other behavioral facts an agent would want for a no-annotation tool: whether it is a pure read, what happens with an invalid or ambiguous filename, and whether the whole outline is returned or truncated.

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?

Two short sentences with zero filler; the scope ('only headings and line numbers') is front-loaded before the usage hint. Every clause carries information an agent can act on.

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 both what is returned and why one would choose it over full-document reads. The remaining gap is failure behavior for a bad filename, which matters slightly more here because no annotations declare the read-only profile.

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% and the single parameter already documents 'Exact .md guide filename.' The description only reinforces the single-guide scoping ('from one guide') without adding format, casing, or ambiguity-resolution detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 verb and narrow resource: 'List only section headings and their line numbers from one guide.' That tells an agent exactly what comes back, which differentiates it in spirit from get_blender_reference (full document) and get_blender_reference_excerpt. It stops short of naming those siblings, so the differentiation is inferential rather than explicit.

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?

'Low-context alternative to reading the full document' implies the selection condition (use when you only need navigation/outline, not content), which is useful. However, it never names get_blender_reference or get_blender_reference_excerpt as the alternatives, nor does it state when this tool is the wrong choice, leaving routing to inference.

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