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chrischall

myhotlunchbox-mcp

by chrischall
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TypeScript
Remote

mhlb_update_student

Update a student profile by sending the full student form model with your edits, then confirm the preview to save changes. Fetch the form first because omitted fields are replaced.

Instructions

Update a student profile. Call mhlb_get_student_form first and send that model back with your edits — the endpoint replaces the whole record, so omitted fields are lost. 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
studentYesThe student model — the `data` object returned by mhlb_get_student_form / mhlb_new_student_form — with your edits applied.
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 / student / description
      Previous value: -"The student model, as returned by mhlb_get_student_form / mhlb_new_student_form, with your edits applied."New value: +"The student model — the `data` object returned by mhlb_get_student_form / mhlb_new_student_form — with your edits applied."
  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

A3.6/5.0
Behavior1/5

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

The description states 'the endpoint replaces the whole record, so omitted fields are lost,' which is an overwrite of existing data — exactly the destructive-update behavior the spec assigns to destructiveHint=true. The annotations declare destructiveHint=false (additive updates only), so the description contradicts structured data, despite otherwise rich disclosure of the confirmation flow and unverified status.

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?

Front-loads the purpose, then prerequisite, then confirmation mechanics, then the verification caveat — a sensible priority order with no filler sentences. It is dense and fairly long, but each clause carries operational information (confirmToken lifecycle, preview inspection), so the length is largely earned.

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 no-output-schema, nested-object mutation tool, the description covers everything an agent needs: input provenance, whole-record replacement risk, both confirmation modes, token reuse rules, and the UNVERIFIED caveat. Nothing material is left for the agent to infer.

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% and both parameters are documented inline (the student model and the confirmToken semantics and constraints). The description adds framing about where the student object originates but no syntax or format detail beyond the schema, so the baseline 3 applies.

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 ('Update a student profile') and immediately reveals the mechanism that separates it from siblings: it consumes the model returned by mhlb_get_student_form rather than raw fields. An agent can distinguish this from mhlb_create_student / mhlb_new_student_form without opening any schema.

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?

Gives an explicit prerequisite workflow ('Call mhlb_get_student_form first and send that model back') and fully describes the confirmation path in both elicitation and token-fallback modes, naming MCP_CONFIRM_MODE. It lacks an explicit statement of when to prefer this over creating a new student, but the use context is otherwise unambiguous.

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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