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Santismm Knowledge — Harness Engineering, Agentic AI & Governance

by com.santismm
OverviewDiscussionsAdmin

Get one SANTISMM Lab definition

get_lab
Read-onlyIdempotent

Get one Lab by slug, including formulas, assumptions, related SANTISMM content and its executable endpoint when one exists. Use this after list_labs or search_all; use the named calculate_* tool rather than reimplementing a published formula.

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": {
      "slug": "<slug>"
    },
    "name": "get_lab"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesLab slug, e.g. 'evaluation-sample-size'.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With annotations already declaring readOnly, idempotent, and non-destructive behavior, the description adds meaningful context about what the response will contain and notes the conditional executable endpoint. It does not overload with safety claims but supplies useful behavioral detail beyond the structured annotations.

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 sentences carry the essential information with no waste: what the tool returns, when to call it, and which sibling tool to prefer for formula computation. The most important scoping is front-loaded in the first sentence.

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

Completeness5/5

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

For a simple single-parameter fetch tool, the description fully equips an agent: it names the resource, the lookup key, the included content, the conditional endpoint, and the appropriate usage sequence. The presence of an output schema removes the need to describe return fields further.

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 description coverage is 100%, so the schema already documents the slug parameter with an example. The description adds no new parameter semantics beyond saying 'by slug', but that is acceptable since the schema covers it completely.

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?

The description uses a specific verb and resource ('Get one Lab by slug') and enumerates the payload contents: formulas, assumptions, related SANTISMM content, and executable endpoint when present. It clearly differentiates from list_labs (listing) and calculate_* tools (computing formulas) among the sibling set.

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?

The description explicitly instructs when to use this tool: 'Use this after list_labs or search_all'. It also names the alternative category ('the named calculate_* tool') and directs agents not to reimplement published formulas, giving clear routing guidance relative to siblings.

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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