mindmap-nimbokit

add_arrows

Add relationship arrows connecting two ideas with an optional description label (concept map relationship). Apply selectively when there is a genuine causal link, cycle, or dependency across branches. Do NOT connect parent and child.

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": {
      "projectId": "<projectId>"
    },
    "name": "add_arrows"
  }
}

Input Schema

Name	Required	Description
`to`	No	Target node text/keyword (alternative to toId)
`from`	No	Source node text/keyword (alternative to fromId)
`toId`	No	Target node ID (or use "to" with node text)
`arrow`	No
`label`	No	Relationship label (e.g. "leads to", "depends on")
`style`	No
`fromId`	No	Source node ID (or use "from" with node text)
`projectId`	Yes	The project ID or the full Canvas URL (including the #map=... hash). Passing the full Canvas URL ensures 100% reliable state recovery across turns.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden; it does communicate the semantic constraint and selectivity of the operation. However, it does not state that the operation mutates persisted project state, how node-text resolution failures behave, whether duplicate/parallel arrows are allowed, or what default direction/style is applied. Useful context, but significant behavioral gaps remain.

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 tight sentences: what it does first, then when to apply, then the hard exclusion. No filler, and the most decision-relevant constraint (parent/child) is placed last for emphasis without burying the core purpose.

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?

For an 8-parameter mutation with no annotations and no output schema, the description should explain defaults and failure modes; it explains semantics well but leaves enum behavior and return/error behavior unstated. Adequate to call the tool, not complete.

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 75%, so most parameters carry their own descriptions and the baseline is 3. The description adds only that the label is optional, while the two enum parameters (arrow: end/both/none, style: solid/dashed/dotted) are undocumented in both schema and description — a meaningful gap for a graph tool where directionality matters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Add relationship arrows connecting two ideas') plus the domain framing ('concept map relationship'), which cleanly separates it from siblings like add_nodes or update_node. An agent can tell this creates edges, not nodes, without opening the schema.

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

Usage Guidelines5/5

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

Gives an explicit positive condition ('genuine causal link, cycle, or dependency across branches') and an explicit exclusion ('Do NOT connect parent and child'), plus a selectivity directive. This is exactly the when/when-not guidance an agent needs to avoid over-creating edges.

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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