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joiva_confirm_planned

DestructiveIdempotent

Confirm a planned Joiva meal (by its entryId) as actually eaten. It is logged with the time of confirmation (not the planned time) and now counts towards the day's totals. grams corrects the portion.

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": {
      "entryId": "<entryId>"
    },
    "name": "joiva_confirm_planned"
  }
}

Input Schema

NameRequiredDescriptionDefault
gramsNoCorrected portion, if it differed from the plan
entryIdYes
unitCountNoHow many of that unit.
unitLabelNoUnit of the corrected portion, e.g. 'Ei M'. Only takes effect together with `grams`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

The description adds useful behavior beyond the annotations: logging uses the confirmation time rather than the planned time, the entry counts toward the day's totals, and grams can correct the portion. It does not explain the destructiveHint=true behavior, such as what is replaced or removed, nor does it describe auth or rate-limit behavior.

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?

Three short sentences front-load the core action and follow with the key behavioral consequences. There is no filler or unnecessary repetition.

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

Completeness3/5

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

The description covers the main action, timing semantics, totals impact, and grams correction, which is adequate for invoking the tool. It is less complete for a destructive, idempotent mutation because it does not clarify what is destroyed or how repeated confirmation behaves, though the idempotent annotation partially covers the latter.

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 75%, so the schema already documents most parameters. The description only adds meaning for entryId and grams, while unitCount and unitLabel are left to the schema.

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 states a specific verb and resource: confirm a planned meal as eaten, keyed by entryId. It is clear what the tool does, though it does not explicitly contrast itself with nearby siblings such as joiva_log_meal or joiva_skip_meal.

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 implied by 'confirm a planned Joiva meal ... as actually eaten,' which tells the agent when this tool applies. However, there is no explicit when-not guidance or named alternative for cases such as skipping the meal or logging a non-planned food.

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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