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Get user profile

get_user_profile
Read-only

Profile snapshot: CEFR level, target/source languages, due card count, weak words, recent lookups. Pass lang to scope the snapshot to one learning language (for users learning several); omit it for the user's primary language.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoOptional ISO or BCP-47 tag (en, en-us, pt-br). Scopes the whole profile - level, due count, weak words - to that learning language. Omit for the user's primary language.

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already signals a safe read operation, and the description adds contextual detail about how the `lang` parameter scopes the entire snapshot and the fallback to the primary language. This goes beyond the annotation without contradicting it, though it does not disclose potential error conditions or response structure.

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?

The description is two sentences long, with the first sentence front-loading the key contents and the second providing parameter guidance. Every word earns its place with no redundancy or filler.

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 absence of an output schema, the description carries the burden of explaining what the tool returns, and it does so by listing the main fields. The optional parameter behavior is fully covered. It could be enhanced by noting the return type (e.g., 'returns a profile object'), but the current level is sufficient for a simple read-only tool.

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?

The input schema provides thorough documentation for the single `lang` parameter, including examples and the omission behavior. The description largely restates the same information, so it adds minimal new semantic value beyond the schema's high coverage.

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 'Profile snapshot' and enumerates the specific data included (CEFR level, languages, due card count, weak words, recent lookups), making the tool's function unambiguous. It also differentiates from sibling getters like get_card and get_queue by presenting a composite overview rather than a single resource.

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

Usage Guidelines4/5

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

The description explicitly explains when to pass `lang` versus omit it, providing clear usage guidance for the optional parameter. It implicitly distinguishes this tool from more specific getters by framing it as a profile snapshot, though it does not explicitly name alternatives or exclusions.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools cleanly separate single-card lookup, batch lookup, due queue, event log, and SRS adjustments. The main overlap is `get_system_instructions` and `get_user_profile`, which both return CEFR level, languages, due count, and weak words, so an agent could mis-select between them.

Naming Consistency5/5

Every tool follows a consistent lowercase snake_case verb_noun pattern: capture_*, get_*, mark_*, log_*, check_. The verbs are descriptive and predictable, making the set easy to navigate.

Tool Count5/5

13 tools is well within the ideal scope for a language-learning memory/assistant server. Each tool covers a distinct part of the capture, lookup, review, and spaced-repetition workflow without feeling padded.

Completeness4/5

The core lifecycle is well covered: grammar and vocabulary capture, batch deck checks, card detail, due queue, recent activity, and SRS boosts/penalties. Minor gaps exist: captured grammar mistakes have no retrieval endpoint, and there is no delete/dismiss path for unwanted cards, but agents can work around these.