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sameerbajaj

AnkiWeb MCP

by sameerbajaj
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learnings_candidates

Read-only

Lists auto-captured improvement candidates awaiting judgment; filter by class or status to review and confirm or reject them.

Instructions

List auto-captured improvement candidates awaiting judgment

Input Schema

NameRequiredDescriptionDefault
csvNoOutput as CSV (table and array responses) (default: false)
yesNoSkip confirmation prompts (explicit confirmation for scripts) (default: false)
jsonNoOutput as JSON (default: false)
agentNoSet agent-friendly output defaults (--json --compact --no-input --no-color) (default: false)
classNoFilter by class (flag_alias | playbook_candidate)
limitNoMaximum rows to return (default: capped) (default: 0)
plainNoOutput as plain tab-separated text (default: false)
quietNoBare output, one value per line (default: false)
selectNoComma-separated fields to include in output (e.g. --select id,notetype_id,deck_id)
statusNoFilter by status (open | confirmed | rejected | expired; empty for all) (default: open)
compactNoReturn only key fields (id, name, status, timestamps) for minimal token usage (default: false)
dry-runNoShow request without sending (default: false)
max-ageNoMaximum acceptable age of local-store data before a stderr hint suggests sync; 0 disables (default: 30m0s)
receiptNoWrite an atomic private run receipt (default: false)
timeoutNoRequest timeout (default: 1m0s)
no-cacheNoBypass response cache (default: false)
no-colorNoDisable colored output (default: false)
no-inputNoDisable all interactive prompts (for CI/agents) (default: false)
no-learnNoDisable the teach/recall learning loop for this invocation (default: false)
idempotentNoTreat already-existing create results as a successful no-op (default: false)
rate-limitNoMax requests per second (0 to disable; default auto — pace to server rate-limit headers) (default: auto)
data-sourceNoData source for read commands: auto (live with local fallback), live (API only), local (synced data only) (default: auto)
client-profileNoSelect the tenant-gated client profile (env: ANKIWEB_CLIENT_PROFILE)
human-friendlyNoEnable colored output and rich formatting (default: false)
allow-partial-failureNoDowngrade response-body partial-failure (e.g. partialFailureError) to a warning instead of a non-zero exit (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds that candidates are 'auto-captured' (origin) and pending judgment (state), which is useful context, but says nothing about the default 'open' filter behavior, freshness of local-store data, or result shape.

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?

A single seven-word sentence with zero waste, and the key qualifier ('awaiting judgment') is front-loaded. Nothing to trim.

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?

For a read-only list tool with full schema coverage and no output schema, most of what an agent needs is present. The remaining gap is conceptual: it never defines what a 'candidate' is relative to learnings_list entries, which matters for tool selection among five learnings_* siblings.

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 description coverage is 100% across all 25 parameters, including class, status, limit, and compact, so the schema does the heavy lifting. The description adds no parameter-level meaning beyond what is already documented, making the baseline 3 appropriate.

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 specific verb and resource ('List auto-captured improvement candidates') plus a scope qualifier ('awaiting judgment'), so the agent knows what comes back. However, it does not distinguish itself from the sibling learnings_list, which an agent could easily confuse it with.

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?

The phrase 'awaiting judgment' hints at a review workflow, but the description never says when to call this instead of learnings_list, or that the natural follow-up is learnings_confirm / learnings_reject. No exclusions or prerequisites are given.

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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