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Eduvent

Anki Card Manager (acm)

by Eduvent

acm_resolve

Resolve Anki review queue items with approve, reject, purge, or correct actions. Corrected cards automatically re-enter the deduplication and classification pipeline.

Instructions

Resuelve un item de la cola de revisión con UNA sola acción (E5-1 / E5-3).

Funciona en CUALQUIER estado (id completo o prefijo), no solo en la cola activa (§6). La cola incluye duplicados posibles y clasificación ambigua.

Args: record_id: ID completo o prefijo del registro. action: "approve" (→ aprobada), "reject" (→ descartada), "purge" (borrado físico del registro) o "correct". front, back: contenido corregido (requeridos para action="correct"). tags: tags sugeridos para la corrección (opcional, "category::value"). note_type, deck: corrección opcional de modelo/mazo (§5).

Para "correct", la card corregida REINGRESA al pipeline: se re-deduplica y re-clasifica automáticamente (E5-3).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
backNo
deckNo
tagsNo
frontNo
actionYes
note_typeNo
record_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: actions include physical deletion (purge), and 'correct' causes re-ingestion with re-deduplication/re-classification. It also states it works with any ID completeness. However, side effects of other actions (e.g., approve) are not detailed.

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 concise and front-loaded with the purpose (single action to resolve item). It structures arguments in a clear list. References to internal sections (§5, §6, E5-1/E5-3) add domain-specific conciseness but may be cryptic without context.

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

Completeness4/5

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

Given 7 parameters and no output schema visible but indicated as present, the description covers the tool's purpose, actions, parameter dependencies, and re-ingestion behavior. It lacks explanation of return values (but output schema exists) and error conditions, yet is sufficient for correct invocation.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains all 7 parameters: record_id (ID or prefix), action (4 values with results), front/back (required for correct), tags (optional format), note_type/deck (optional correction). The description adds meaning beyond the schema, though note_type/deck reference an external section (§5) without full explanation.

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 clearly states it resolves an item from the review queue with a single action, listing specific actions (approve, reject, purge, correct). It distinguishes itself from siblings like acm_review by noting it works in any state, not just the active queue. However, it does not explicitly differentiate from all sibling tools, leaving some ambiguity.

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 usage for resolving review queue items and explains behavior for each action (e.g., 'correct' re-enters pipeline). It mentions it works in any state but does not provide explicit guidance on when to use this tool over alternatives like acm_review or acm_annotate. No 'when not to use' or alternatives are mentioned.

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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