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load_toolset

Load the documentation and input schemas for a deferred toolset. Most ctlsurf tools are listed directly, but specialty toolsets are deferred to keep the tool list small. Call this when you need one of them, then invoke the returned tools via ctlsurf_call(tool_name, arguments).

Available toolsets:

  • dashboards (18 tools): Business: group dashboards with change-order, proposal/SOW and ticket cards, documents, rollups and pinned live blocks

  • datastore (14 tools): Agent working data: typed-column data tables with row operations, key-value state blocks, append-only logs

  • graphs (12 tools): Diagrams: react-flow node graphs, ER diagrams (DB schemas, API contracts, domain models), tree nodes

  • presentations (7 tools): Slide decks: create presentations, add structured slides from templates, export to .pptx

  • skills (12 tools): Agent playbooks: create, search, fork and share reusable workflow definitions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolsetYesToolset to load

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / toolset / enum
      Previous value: -[
      -  "datastore",
      -  "graphs",
      -  "presentations",
      -  "skills"
      -]New value: +[
      +  "dashboards",
      +  "datastore",
      +  "graphs",
      +  "presentations",
      +  "skills"
      +]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the key behavior: this is a two-step discovery step whose output must be invoked through ctlsurf_call, and it states what is returned (documentation plus input schemas). It does not say whether loading has side effects, is cached, or is idempotent, which is a minor remaining gap for a loader.

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?

Front-loaded with purpose and the routing instruction, and the toolsets list earns its length because it is the only place the enum values are explained semantically. Minor redundancy in 'Call this when you need one of them' against the preceding sentence keeps it from a 5.

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?

No output schema and no annotations, but the description compensates by explaining the discovery-then-invoke flow and summarizing what each toolset contains. It never shows the shape of the returned payload, which is the one thing an agent might still want before calling.

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

Parameters4/5

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

Schema coverage is 100% and the enum is self-documenting, so the baseline would be 3. The description goes beyond that by annotating each enum value with its tool count and content domain (e.g. 'dashboards (18 tools): group dashboards with change-order, proposal/SOW and ticket cards'), which genuinely helps the agent pick the right value.

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 ('Load the documentation and input schemas for a deferred toolset') and immediately explains the deferred-toolset mechanism that distinguishes it from the directly-listed sibling tools. An agent can tell exactly what it retrieves 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 trigger ('Call this when you need one of them') and an explicit follow-up ('then invoke the returned tools via ctlsurf_call(tool_name, arguments)'). It also explains why the toolsets are deferred, which is the condition under which this tool rather than a direct sibling call applies.

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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