The Comp Desk Builder

NY SLU % for a joint replacement

calculate_slu_joint_replacement

Read-onlyIdempotent

The schedule loss of use percentage for a shoulder, hip or knee replacement on its own scoring track (2018 NY Impairment Guidelines Tables 5.5 / 6.5 / 7.5, as the app's engine encodes them): the base, plus the value that most closely matches the deficit in each column (range of motion, position, atrophy, chronic complications), up to the table maximum. A failed replacement is reported as not schedulable. Shoulder takes flexion/abduction; hip takes flexion, leg-length discrepancy, mal-rotation, hip_fracture; knee takes flexion, extension contracture, malalignment, ML laxity, AP motion, leg length. New York State only. Computes with The Comp Desk calc-core, the same engine as the app and the Pro Workspace; it never estimates. A missing input returns status "missing" and nothing is calculated. Returns the figures, the steps with the rule and engine function behind each, and the not-legal-advice notice. Needs your builder key. Same engine the Pro Workspace tiles call through CD.Calc, so a figure here matches the app to the cent.

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": {
      "joint": "<joint>"
    },
    "name": "calculate_slu_joint_replacement"
  }
}

Input Schema

Name	Required	Description
`joint`	Yes
`failed`	No	The replacement failed (not schedulable).
`ap_motion_mm`	No	Knee: anterior-posterior motion, millimetres.
`hip_fracture`	No	Hip: the replacement followed a fracture.
`atrophy_inches`	No	Atrophy, inches (mid-arm for the shoulder, mid-thigh for hip/knee).
`months_post_op`	No	Months since the replacement (the engine warns under its minimum).
`flexion_degrees`	No	Flexion, degrees.
`abduction_degrees`	No	Shoulder: abduction, degrees.
`ml_laxity_degrees`	No	Knee: medial-lateral laxity, degrees.
`mal_rotation_degrees`	No	Hip: mal-rotation, degrees.
`malalignment_degrees`	No	Knee: malalignment, degrees.
`chronic_complications`	No
`extension_contracture_degrees`	No	Knee: extension contracture (flexion deformity), degrees.
`leg_length_discrepancy_inches`	No	Hip or knee: leg-length discrepancy, inches.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations already declare a safe, idempotent, closed-world read, and the description goes well beyond that: it discloses the auth requirement ('Needs your builder key'), the determinism guarantee ('it never estimates'), the missing-input behavior (status 'missing', nothing calculated), the non-schedulable path, and the contents of the response including per-step rule and engine function plus a not-legal-advice notice. That is exactly the extra context the annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence is dense and front-loads the core purpose, but the closing third is redundant: the engine identity is asserted twice ('Computes with The Comp Desk calc-core...' then 'Same engine the Pro Workspace tiles call through CD.Calc... to the cent'). Condensing those into one claim would remove roughly a fifth of the text with no loss.

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?

With 14 parameters and no output schema, the description carries the return-value burden and does so (figures, annotated steps, notice) while also covering the missing-input and failed-replacement branches. What remains thin is the warning behavior around months_post_op, which the description only gestures at indirectly.

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 86%, so the baseline is 3; the description earns more by mapping parameters to joints (shoulder = flexion/abduction, hip = flexion, leg-length discrepancy, mal-rotation, hip_fracture, knee = flexion, extension contracture, malalignment, ML laxity, AP motion, leg length). That conditional applicability is the one thing the flat schema cannot express, since all 14 fields are siblings with no joint gating.

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 names a specific computation (schedule loss of use percentage) and a specific resource class (shoulder, hip or knee replacement) with its governing tables (5.5 / 6.5 / 7.5), and it flags the out-of-scope case (failed replacement = not schedulable). It never names a sibling such as calculate_slu_percent_from_rom or calculate_slu_award, so the agent must infer the boundary from the joint-replacement framing alone.

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?

Usage is implied rather than stated: 'New York State only' and the joint enum tell the agent this is the NY replacement track, and the failed-replacement sentence covers one exclusion. There is no explicit instruction on when to prefer this over the ROM-based or award siblings, so a routing decision remains partially to inference.

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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