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Identify knowledge consolidation with deck maturity and Interest Heat Score, highlighting genuine interest and study consistency. Syncs with AnkiWeb to include mobile reviews.

Instructions

Show learning progress: deck maturity, Interest Heat Score, study consistency.

Interest Heat Score ranks tags by how well knowledge consolidates — high scores reveal where genuine interest lives (effortless retention).

Syncs with AnkiWeb first to include mobile reviews.

Args: deck: Optional deck name to scope the report (default: all decks) top_n: Number of top tags to show in heat ranking (default: 15)

Returns: Markdown report with deck overview, interest heat, and study streak

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deckNo
top_nNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The annotations declare readOnlyHint=true, and the description adds valuable context about the automatic AnkiWeb sync and the Markdown report format. It also explains the Interest Heat Score semantics, which goes beyond the bare annotation boundary.

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 description is well-organized with a summary, a brief explanatory note, and an Args/Returns section. The Interest Heat Score explanation adds useful context but could be tightened; overall it remains focused and efficiently worded.

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?

The description covers the tool's purpose, parameter meanings, return format, and a key behavioral trait (sync). Given the presence of an output schema and readOnly annotation, this is sufficient and complete for an agent to use the tool effectively.

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

Parameters5/5

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

The input schema has no parameter descriptions (0% coverage), but the description compensates fully by explaining both 'deck' (scope to a specific deck, default all) and 'top_n' (number of tags in heat ranking, default 15). This provides complete semantics and defaults.

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?

The description opens with 'Show learning progress: deck maturity, Interest Heat Score, study consistency,' which precisely identifies the tool's function. It distinguishes itself from sibling tools like list_decks by focusing on analytical progress metrics rather than raw deck listing.

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?

The description implies the tool is used for viewing learning progress, but it does not explicitly state when to choose it over alternatives like list_decks or sync. The sync behavior is mentioned, but there are no direct comparisons or exclusionary guidance.

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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