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anki-workflow-mcp

anki-workflow-mcp

by Gugart43

Topic Budget Plan

topic_budget_plan

Calculates a top-down total card budget for a topic from source text and clinical decisions, then plans upfront and splits cards into strict batches of 20.

Instructions

Calculate top-down total card budget for a topic based on source text and clinical decisions. Plans total cards upfront and chunks strictly into batches of 20 (MAX_BATCH = 20).

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": {
      "deck_dir": "<deck_dir>"
    },
    "name": "topic_budget_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNo
labelNo
deck_dirYes
batch_sizeNo
card_textsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one real behavioral trait: output is chunked strictly into batches capped at 20 (MAX_BATCH). However it never says whether files are written under deck_dir, whether existing budgets are overwritten, or what permissions are needed, and the hard 'strictly batches of 20' claim sits oddly against a configurable batch_size parameter.

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?

Two tight sentences with no filler, front-loading what is computed before describing the batch constraint. Slightly dense phrasing ('based on source text and clinical decisions') without saying where those come from, but nothing is redundant.

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?

An output schema exists so return values need not be explained, but for a 5-parameter planning tool with no annotations and 0% schema coverage, the description omits the meaning of four of five inputs and all side effects on deck_dir. An agent would be guessing when invoking it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across five parameters, so the description must compensate and largely does not. It alludes to text ('source text') and batching, but leaves label, deck_dir, card_texts, and the distinction between batch_size and MAX_BATCH undefined.

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?

States a concrete verb and resource: 'Calculate top-down total card budget for a topic'. It also names its inputs (source text, clinical decisions) and its output shape (total cards, chunked batches), so an agent can tell it apart from the sibling batch/count tools without opening the schema, though no sibling is named explicitly.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance and no named alternative. The phrase 'Plans total cards upfront' only weakly implies it belongs before batch drafting steps; an agent must infer sequencing relative to siblings such as count_batch_cards or batch_patch_draft.

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