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myhotlunchbox-mcp

by chrischall
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

mhlb_update_order

Revise an existing school lunch order by fetching it first, applying your edits, then confirming the full replacement before it is submitted.

Instructions

Change an existing lunch order. Call mhlb_get_order first and send that model back with your edits — the endpoint replaces the whole order. Asks the user to confirm first: a confirmation prompt where the client supports one; otherwise the first call returns a preview and a confirmToken, and only a repeat call with that token proceeds (see MCP_CONFIRM_MODE). NOTE: this write is UNVERIFIED — its request shape was derived from the web app’s compiled API client but has not been exercised against a live account. Inspect the confirmation preview before approving it.

Input Schema

NameRequiredDescriptionDefault
orderYesThe order model — the `data` object returned by mhlb_get_order_form / mhlb_get_order — with quantities and options edited.
confirmTokenNoONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 "confirmation-required" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.7
    • changedInput schema / properties / order / description
      Previous value: -"The order model, as returned by mhlb_get_order_form / mhlb_get_order, with quantities and options edited."New value: +"The order model — the `data` object returned by mhlb_get_order_form / mhlb_get_order — with quantities and options edited."
  2. Changed2 schema fields changedv1.2.1
    • removedInput schema / properties / confirm
      Removed value: -{
-  "description": "Must be true to proceed. Without this, the tool returns a preview.",
-  "type": "boolean"
-}
    • addedInput schema / properties / confirmToken
      Added value: +{
+  "description": "ONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 \"confirmation-required\" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.",
+  "type": "string"
+}
  3. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  4. First observedv0.2.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and openWorldHint=true, but the description adds substantial non-obvious context: the endpoint replaces the entire order (not a partial patch), a user confirmation is required, and the write is UNVERIFIED against a live account. The only minor gap is it doesn't state what the preview/response actually contains, but the confirmation flow and unverified warning are exactly the kind of disclosure that matters here.

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?

The verb and core action are front-loaded, and the remaining clauses (confirmation flow, unverified note) each carry necessary operational detail. It is dense and somewhat long for a single paragraph, but no sentence is filler given the multi-step confirmation behavior it must convey.

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 write tool with a non-trivial confirmation handshake, no output schema, and a nested order object, the description covers the essential behaviors: prerequisite call, whole-model replacement, elicitation vs. token fallback, and the unverified caveat. Nothing an agent needs to invoke it safely is missing.

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 both parameters carry detailed inline descriptions, so the baseline is 3. The description adds real meaning by explaining that the `order` value must be the model returned by mhlb_get_order (with edits) and that `confirmToken` comes only from a phase-1 preview and is never reused — reinforcing rather than merely restating the schema.

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 ("Change an existing lunch order") that cleanly separates it from the sibling create_order, delete_order, and get_order tools. An agent can identify it as the mutation path for an existing order 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?

Explicitly names the prerequisite ("Call mhlb_get_order first and send that model back with your edits"), explains the replacement semantics, and lays out the two confirmation paths including the exact fallback sequence. When-to-use and how-to-sequence are fully specified rather than inferred.

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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