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joiva_unskip_meal

DestructiveIdempotent

Undo a skipped meal slot: the slot becomes an open question again for that day.

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": {
      "label": "<label>"
    },
    "name": "joiva_unskip_meal"
  }
}

Input Schema

NameRequiredDescriptionDefault
tzNoIANA timezone, default Europe/Berlin
dateNo
labelYesMeal slot label

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, idempotentHint=true and readOnlyHint=false, so the safety profile is covered. The description usefully clarifies the effect (the slot reverts to an open question), but it does not address what happens to any food already logged against the skipped slot, nor permissions or error behavior, which matters for a destructive mutation.

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?

A single tight sentence with the outcome front-loaded after the verb; nothing is wasted. It is perhaps slightly too terse for a destructive mutation, but structurally clean.

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

Completeness2/5

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

For a destructive, non-read-only mutation with no output schema, the description should say what is destroyed or reverted (logged entries? planned food?) and what the caller gets back. Annotations cover idempotency and destruction at a high level, but an agent still cannot predict side effects on existing data.

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 coverage is 67%: label and tz are described in the schema, while date carries only a regex pattern with no explanation. The description adds no parameter-level meaning at all, so with the schema doing the heavy lifting the baseline 3 is appropriate.

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 pairs a specific verb ("Undo") with a specific resource (a skipped meal slot) and states the resulting state, so an agent can distinguish it from joiva_skip_meal without opening either schema. It stops short of naming the inverse sibling explicitly, which would have made it a 5.

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 only implied: the inverse relationship to skipping a meal is inferable from "Undo a skipped meal slot," but there is no explicit when-to-use statement, no prerequisite (e.g., a slot must currently be skipped), and no mention of alternatives such as re-planning the meal via joiva_plan_food or joiva_confirm_planned.

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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