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MindDory Brain

by com.minddory

Capture grammar mistake

capture_grammar_mistake

Log a grammar mistake the user just made in the target language, creating a grammar point in their Minddory deck. Use it proactively whenever the user writes a target-language sentence with a clear, correctable error (wrong tense, agreement, word_choice, word_order, missing or wrong article, preposition, gender, conjugation, spelling, pluralization). By connecting Minddory the user opted IN to automatic capture, so log it as you go - do not ask permission first or turn it into a yes/no question. The user connected Minddory to catch and review these patterns; you do not need to announce each log. Pass the original text + correction + error_type. Multiple mistakes in one message = multiple calls.

VARIANT RULE: Always pass the user's full BCP-47 variant in the lang field (e.g. en-gb, not en) - get it from get_system_instructions on first turn. Before logging, check that the "error" is not actually a valid regional variant form (US past-simple vs UK present-perfect with "just/already", US "in the hospital" vs UK "in hospital", US "color" vs UK "colour", BR gerund vs PT "a + infinitive", etc.). When the variant is unspecified (base ISO only), treat ALL regional forms as valid. Better to skip a borderline call than to mark a valid variant form as wrong.

error_type must be one of: tense, agreement, word_choice, word_order, article, preposition, spelling, pluralization, conjugation, gender, other. Feeds the user's Grammar Patterns view at app.minddory.com/grammar.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoISO target language code.
user_textYesThe exact erroneous sentence/phrase the user wrote.
correctionYesThe corrected sentence/phrase.
error_typeNoOne of: tense, agreement, word_choice, word_order, article, preposition, spelling, pluralization, conjugation, gender, other.
explanationNoShort rationale (1-2 sentences). Optional.

TDQS

A5/5.0
Behavior5/5

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

With annotations only indicating readOnlyHint=false and destructiveHint=false, the description adds rich behavioral context: proactive logging without user confirmation, respecting opt-in consent, passing the full BCP-47 variant, and handling regional variation nuances. It also explains the downstream impact on the Grammar Patterns view.

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?

Though substantial, every sentence earns its place, covering purpose, proactive use, regional variant rules, error_type list, and integration output. The description is front-loaded with the core action and then details edge cases, making it well-structured and appropriately sized for the tool's complexity.

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?

With 5 parameters and no output schema, the description fully addresses context: what the tool does, when to invoke it, how to handle ambiguous regional variants, which error_type to select, and where the result appears. No critical information is missing for an agent to select and invoke the tool correctly.

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?

Schema coverage is 100%, but the description adds critical semantics beyond the schema, especially for the `lang` parameter, requiring the full BCP-47 variant (en-gb, not en) and instructing to retrieve it from get_system_instructions. It also reinforces the allowed error_type values and which parameters to pass, going beyond bare schema definitions.

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 the tool logs a grammar mistake and creates a grammar point in the user's Minddory deck. It specifies the exact resource (grammar point) and verb (log/create), and distinguishes it from sibling tools like capture_word by focusing on grammar errors.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: 'Use it proactively whenever the user writes a target-language sentence with a clear, correctable error.' It also includes when-not-to-use (skip borderline calls, validate regional variants) and instructs not to ask permission or announce logs. This is comprehensive and actionable.

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.

Resources