Skip to main content
Glama

get_examples

Retrieve sample flashcards from Anki to guide creation of new cards. Filter by deck and choose from sampling methods like recent or most reviewed.

Instructions

Get example notes from Anki to guide your flashcard making. Limit the number of examples returned and provide a sampling technique:

    - random: Randomly sample notes
    - recent: Notes added in the last week
    - most_reviewed: Notes with more than 10 reviews
    - best_performance: Notes with less than 3 lapses
    - mature: Notes with interval greater than 21 days
    - young: Notes with interval less than 7 days

Args:
    deck: Optional[str] - Filter by specific deck (use exact name).
    limit: int - Maximum number of examples to return (default 5).
    sample: str - Sampling technique (random, recent, most_reviewed, best_performance, mature, young).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deckNo
limitNo
sampleNoSampling technique: random, recent (added last 7d), most_reviewed (>10 reps), best_performance (<3 lapses), mature (ivl>=21d), young (ivl<=7d)random

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, but the description clearly indicates a read-only operation (getting examples). It does not disclose permissions or side effects, but for a retrieval tool, this is acceptable.

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 brief intro, a bulleted list of sampling techniques, and an args section. It is efficient but could be slightly more concise by removing redundant wording.

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 the tool's complexity (3 parameters, no annotations, output schema exists), the description adequately covers purpose and parameter details. It does not discuss return format, but the output schema likely handles that.

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 description adds significant meaning beyond the schema: it explains the purpose of each parameter (deck as exact name, limit as maximum, sample with detailed technique definitions). Schema coverage is only 33%, so the description fully compensates.

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 clearly states 'Get example notes from Anki to guide your flashcard making', specifying the action and resource. It distinguishes from sibling tools like search_notes by focusing on high-quality examples.

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 explains parameters and sampling techniques but does not explicitly state when to use this tool versus alternatives like search_notes. Usage context is implied but lacks explicit when-not guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/samefarrar/mcp-ankiconnect'

If you have feedback or need assistance with the MCP directory API, please join our Discord server