Sally Skills

supplement_grading

Sally skill ($0.008/call)

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": {
      "supplements": "<supplements>"
    },
    "name": "supplement_grading"
  }
}

Input Schema

Name	Required	Description
`language`	No	BCP-47 short code (e.g. 'en', 'id'). Omit for auto-detect from the stack text.
`use_labs`	No	If true (default), the agent may read the calling user's lab results to surface biomarker-relevant gaps. Set false for a stack-only audit with no PHI.
`supplements`	Yes	The supplement stack to audit — names + doses as free text or a list (e.g. "vitamin D 5000IU, magnesium glycinate 400mg, fish oil 1g").

Schema Changelog

Changes observed during successful MCP inspections.

AddedJun 12, 2026

TDQS

D1.6/5.0

Behavior1/5

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

No annotations are provided, and the description only mentions cost. There is no disclosure of behavioral traits such as side effects, permissions, or data handling. The description fails to inform the agent about what happens when the tool is invoked.

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

Conciseness2/5

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

The description is extremely short but fails to convey necessary information. Under-specification is not conciseness; the single sentence does not earn its place because it lacks substantive content.

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

Completeness1/5

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

Given the tool has 3 parameters, one required, and lacks an output schema, the description is grossly incomplete. It does not explain the tool's behavior, return values, or how it relates to sibling tools, providing no actionable context for an AI agent.

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 input schema already documents all parameters. The description adds no additional meaning beyond the schema, meeting the baseline for this dimension.

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

Purpose1/5

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

The description "Sally skill ($0.008/call)" does not state what the tool does. It provides a cost and a name but lacks a verb or resource, making it impossible to infer the tool's purpose from the description alone.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives like lookup_supplement_grade. The description offers no context for selection, leaving the agent without any usage criteria.

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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