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davidmosiah

Wellness Nourish

Nourish demo

nourish_demo
Read-onlyIdempotent

Get synthetic sample payloads for food search, meal estimation, and daily summary to verify response contracts before making real calls.

Instructions

Returns synthetic example payloads of nourish_search_food, nourish_estimate_meal, and nourish_daily_summary so agents see the contract before any real call. Shapes are verified against the real pipelines by scripts/demo-contract-test.mjs, so they are safe to write a parser against; inputs shows the call that produced each sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
privacy_modeNosummary = high-level totals without item detail; structured = default full JSON-friendly fields; raw = same as structured for this local store (parity).structured
response_formatNojson

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.2
  2. Removedv0.7.0
  3. First observedv0.6.6

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds valuable behavioral context beyond annotations: the payloads are synthetic, verified against real pipelines by a contract test, safe to write a parser against, and include an `inputs` field. This gives agents actionable information about reliability and output composition.

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 information-dense sentences with zero fluff. The primary action is front-loaded, and the verification claim and `inputs` note are placed logically. Every clause earns its place.

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?

For a simple demo tool with two optional params and no output schema, the description covers the key facts: what is returned, why it is trustworty, and a notable output field. It does not describe the exact payload structure, but agents can infer it from the three referenced contracts. The minor omissions are acceptable.

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?

The description does not explain either parameter, but the schema documents `privacy_mode` well and `response_format` is a self-explanatory enum. With 50% schema coverage, the description adds no parameter value, but the remaining gap is minor because the enum values `json`/`markdown` make the meaning obvious. Overall, the schema does the heavy lifting.

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 opens with a specific verb and object: 'Returns synthetic example payloads' of three named tools. It clearly distinguishes this demo tool from the real sibling tools like nourish_search_food, explaining the purpose as showing the contract before real calls. This is unambiguous and well differentiated.

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

Usage Guidelines4/5

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

The phrase 'so agents see the contract before any real call' gives a clear context for when to use this tool: before invoking the real operations. The named target tools are useful, but the description does not explicitly state when not to use it or point to alternatives for real data, leaving some routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.