miyagi
🥋 miyagi
忍耐強く、ゲーム化され、音声対応のMCPコーディングチューター。 あなたがコマンドを実行します。それは練習させ、修正し、失敗をキャッチし、スコアを記録します。
ワックスを塗って、拭き取る。miyagi は決してあなたの代わりに作業をしません。次のコマンドを手渡し、あなたのレベルに合わせて説明し、すべての結果をレッスンに変えます。各実行はティーチングカードとして返ってきます:ロードマップ上の現在位置、あなたの経験に合わせた What/How/Trade-offs の内訳、Mermaid のメンタルモデル、人々が陥りがちな落とし穴、厳選されたドキュメント、そしてアクティブリコールクイズ。そのすべてが OS の音声エンジンでナレーションされます。
インストールしても安全な理由
あなたのマシンでシェルコマンドを実行するため、信頼する前に読まれるように設計されています。
壊滅的なものは実行されません。
rm -rf、dd of=/dev/*、フォーク爆弾、curl | sh、強制プッシュ、chmod -R 777はパターンマッチされ、呼び出し元のモデルが何を主張しても ドライランに強制されます。このスクリーンは、不注意なユーザーだけでなく、混乱した AI からも防御します。そのため、渡されたis_dangerousフラグを信頼するのではなく、判定を再導出します。拒否リストはバックストップであり、サンドボックスではありません。 実際の境界は、MCP クライアント自身の承認プロンプトであり、コマンドが実行される前にあなたがそれを読みます。スクリーンは、そのプロンプトがうまく処理できない狭いケースのために存在します:クリックして進んでいる人に提案される明らかに破壊的な何か。
失敗はクラッシュする代わりに教えます。 非ゼロの終了コードは、トラブルシューティングラダーを備えたホットフィックス診断を返します。サーバーは決して例外を投げません。
制限付き。 60秒のタイムアウト、4 MBの出力上限、ネットワーク呼び出しなし、テレメトリなし、APIキーなし、アカウントなし。
監査できるほど小さい。 2つのランタイム依存関係(MCP SDK と zod)が、一読できる1つのソースファイルにあります。
Related MCP server: MCP Walkthrough
インストール
MCP クライアントを npx に向けると、初回実行時に取得されます:
npx -y miyagi-mcpまたは、グローバルにインストールすると、miyagi コマンドが使えます:
npm install -g miyagi-mcpgit clone https://github.com/c00p75/miyagi.git
cd miyagi
npm install
npm run build # emits dist/miyagi.js
npm test次に、以下の設定で "command": "node", "args": ["<ABS_PATH>/dist/miyagi.js"] を使用します。
MCP クライアントの設定
3行で、どこでも同じです。キーもアカウントも不要で、すべてローカルで動作します。
{
"mcpServers": {
"miyagi": {
"command": "npx",
"args": ["-y", "miyagi-mcp"]
}
}
}その場所は:
クライアント | ファイル |
Claude Desktop (macOS) |
|
Claude Desktop (Windows) |
|
Cursor |
|
AntiGravity / Windsurf |
|
Claude Code の場合は、1つのコマンドで完了します:
claude mcp add miyagi -- npx -y miyagi-mcpクライアントを再起動して、次のように試してください:「ロードマップをバックエンド開発者に設定して、docker compose config を教えてください。」
内容
エンジン | 説明 |
オーディオ | 非ブロッキングの FIFO キューで、行が互いに話し合うことはありません。何かを話す前に Markdown、URL、絵文字は取り除かれ、OS エンジンは呼び出される前にプローブされるため、バイナリが欠落している場合はサーバーをダウンさせる代わりに静かになります。 |
ロードマップ | カテゴリ、ロードマップ、トピック、ステップ N/M として状態を追跡し、現在地に応じて次のコマンドを提案します。 |
ゲーミフィケーション | コマンドごとに15 XP、正解クイズごとに25 XP(ストリーク乗数あり)、 |
進捗 |
|
安全性 | 呼び出し元とは独立してスクリーニングされる9つのカタストロフクラスがあり、すべてドライランに強制されます。 |
ノート | クイズの正確さと完全なセッションログを含む |
音声エンジン
プラットフォーム | エンジン |
macOS |
|
Windows | PowerShell |
Linux |
|
オーディオが必要な Linux ユーザー: sudo apt install speech-dispatcher。
ツール
quick_config: スキルレベル(ジュニア/ミッド/シニア)、カテゴリ、トラック、トピック、または音声を1回の呼び出しで切り替えます。reset_progress: trueを渡すと、保存された XP を初回実行状態に戻します。set_active_roadmap: カテゴリ、ロードマップ、トピック、ステップカウンターを設定します。get_next_roadmap_command: 次にコピー&ペースト可能なコマンドを取得します。advance: trueで前進します。configure_voice: オーディオの切り替え、1分あたりの単語数の設定、テストフレーズの読み上げget_user_stats: XP、レベル、タイトル、ストリーク、バッジ、タイトルラダーrun_teaching_command: コマンドを実行またはドライランし、ティーチングカードを返します。verify_quiz_answer: クイズを採点し、ストリークと XP を更新し、フィードバックを読み上げます。export_roadmap_notes:ROADMAP_PROGRESS.mdを書き出します。
進捗の保存場所
~/.miyagi/profile.json には、XP、レベル、ストリーク、バッジ、スキルレベル、音声設定、ロードマップの位置が保存されます。ディレクトリは MIYAGI_HOME で上書きできます。これはテストが実際のプロファイルに触れないようにする方法でもあります。
このファイルは読み込み時に信頼されないものとして扱われます。手動で編集可能であり、クラッシュで切り詰められる可能性があるためです。パースに失敗したものはエラーとして発生させる代わりに新しいプロファイルに置き換えられ、範囲外の値は拒否されるのではなくクランプされ、レベルは読み取るのではなく XP から再計算されるため、40 XP でレベル99と主張するファイルは修正されます。書き込みは一時ファイルに行われ、リネームされるため、書き込みが中断されても以前のプロファイルはそのまま残ります。
開発
npm install
npm run typecheck
npm test # node:test, no test framework to install
npm run buildCI は Node 18、20、22 に対して型チェック、テスト、実際の stdio ハンドシェイクを実行します。
知っておくべき制限
コマンドはあなた自身の権限で、あなた自身のディレクトリで実行されます。コンテナも、制限されたユーザーも、システムコールフィルターもありません。これは所有者が操作するローカルな教育ツールには適切ですが、信頼できない入力を受け入れるようになった場合に最初に変更すべき点です。
長時間実行されるコマンドや対話型コマンドは、自分のターミナルで実行してください。60秒の上限で切断されます。
XP とストリークが実際に誰かをロードマップに留めるかどうかは未解決の疑問です。進捗ファイルがあれば、それに答えることができます。
ライセンス
MIT
Available Tools
8 toolsconfigure_voiceConfigure VoiceA
Toggle tutor audio on/off and adjust the speech rate in words per minute.
| Name | Required | Description | Default |
|---|---|---|---|
| enabled | No | ||
| test_phrase | No | Speak this immediately to test the setup. | |
| words_per_minute | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It says the tool toggles audio and adjusts speech rate, but it does not disclose whether settings persist, whether permissions are needed, or what side effects occur. The test_phrase behavior is only in the schema, not the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One efficient sentence with no fluff. The core actions are front-loaded and every word contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, low-complexity configuration tool with zero required parameters and no output schema, the description is mostly sufficient. But it lacks context about persistence, prerequisites, or the full role of test_phrase, and no output schema means the agent is given no clue about the result of calling the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33%, but the description compensates partially by mapping 'toggle on/off' to enabled and 'speech rate in WPM' to words_per_minute. test_phrase is covered by the schema's own description. The added meaning is useful but modest.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Toggle'/'adjust') and names the exact resource ('tutor audio' and 'speech rate'). This clearly separates it from siblings like quick_config and run_teaching_command, which are not voice-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: use this when the user wants to enable/disable tutor audio or change speech rate. However, there is no explicit 'when not to use' statement or mention of alternatives like quick_config, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_roadmap_notesExport Roadmap NotesA
Write a clean ROADMAP_PROGRESS.md summary of the session: roadmap position, player stats, and every concept and command covered.
| Name | Required | Description | Default |
|---|---|---|---|
| append | No | Append instead of overwriting. | |
| output_path | No | File path (relative paths resolve against the server's cwd). | ROADMAP_PROGRESS.md |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does say 'Write', which implies a file mutation, but it does not disclose that the default behavior overwrites an existing ROADMAP_PROGRESS.md, that the file is written to the server's cwd, or any other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence with no filler words. It front-loads the primary verb and deliverable, then specifies the content requirements. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two optional, fully documented parameters and no output schema, so the description covers the core purpose well. However, it omits important behavioral context such as the overwrite-by-default behavior and appropriate invocation timing, leaving mild gaps for an agent deciding when and how to call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters ('append' and 'output_path') are already documented in the schema. The description does not add parameter-specific meaning beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Write'), a specific deliverable ('clean ROADMAP_PROGRESS.md summary'), and the exact content to include ('roadmap position, player stats, and every concept and command covered'). This clearly differentiates it from the sibling tools, none of which are export/summary tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'summary of the session' implies it should be used after a teaching session to persist progress, but there is no explicit guidance on when to invoke it versus alternatives or whether it should be run at the end of every session. Usage is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_next_roadmap_commandGet Next Roadmap CommandB
Suggest the next copy-pasteable terminal command for the active roadmap milestone. Optionally advance the step counter.
| Name | Required | Description | Default |
|---|---|---|---|
| advance | No | Advance step_index by one before suggesting. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits clearly. It does disclose the optional side effect ('Optionally advance the step counter') and implies the command is not executed directly ('copy-pasteable'). However, it does not elaborate on other state changes, error conditions (e.g., missing active roadmap), or the nature of the return value beyond 'suggest a command'. Basic transparency is present but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wordiness. The primary purpose is front-loaded in the first sentence, and the brief second sentence covers the optional parameter. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description covers the main function and side-effect clearly. It does not mention behavior when no active milestone exists, which is a minor gap, but the description is sufficiently complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema's parameter description ('Advance step_index by one before suggesting.') fully documents the 'advance' parameter. The tool description adds only a synonym ('step counter') without new meaning, so it neither compensates for nor expands upon the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Suggest') and resource ('the next copy-pasteable terminal command for the active roadmap milestone'). It is easy to understand the tool's core purpose, but it does not explicitly distinguish itself from sibling tools like run_teaching_command or verify_quiz_answer, so it lacks overt sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions the context ('for the active roadmap milestone') but does not state exclusions, prerequisites, or how it relates to sibling tools such as run_teaching_command. This leaves the agent to infer usage independently.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_user_statsGet User StatsA
Return the current player profile: XP, level, title, quiz streak, unlocked badges, and roadmap progress.
| Name | Required | Description | Default |
|---|---|---|---|
| speak | No | Read the stats aloud. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of indicating behavior. 'Return the current player profile' clearly signals a read-only retrieval with no apparent side effects. It does not detail voice behavior for speak=true, but that is covered by the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence that front-loads the core purpose and then lists return fields. Every word earns its place with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only stats tool, the description is complete: it states what is returned, and the schema fully documents the optional speak parameter. The agent has enough information 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the only parameter 'speak' is fully documented with type, default, and description. The tool description adds no parameter-specific meaning, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Return the current player profile' and enumerates exactly what is included (XP, level, title, quiz streak, unlocked badges, roadmap progress). This clearly differentiates the tool from siblings like verify_quiz_answer or set_active_roadmap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: this tool is used when the current player profile or stats are needed. It does not explicitly discuss when not to use it or name alternatives, but the use case is obvious from the description and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quick_configQuick ConfigC
Instantly switch the target skill level (Junior/Mid/Senior), roadmap category, roadmap track, or topic via simple key-value parameters.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | ||
| skill_level | No | Depth of explanation used in every teaching card. | |
| roadmap_name | No | e.g. "Backend Developer", "Git and GitHub" | |
| current_topic | No | ||
| voice_enabled | No | ||
| reset_progress | No | Wipe saved XP, level, streak and badges back to first-run state. | |
| words_per_minute | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It says 'switch' but gives no indication of side effects, persistence behavior, or the powerful destructive reset_progress option that wipes XP, level, streak, and badges. The schema mentions reset_progress, but the tool description itself does not warn about the impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, but it is more under-specified than genuinely concise. Words like 'Instantly' and 'simple' add little information, and a single vague sentence is not enough for a 7-parameter configuration tool with no annotations and no output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 optional parameters, no annotations, and no output schema, the description is incomplete. It fails to mention the destructive reset behavior, the voice and words_per_minute settings, what happens if multiple parameters are combined, or what response the agent can expect after the call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 43%, so the description should compensate. It maps a few natural-language labels to parameters (skill_level, category, roadmap_name, current_topic), but it omits voice_enabled, words_per_minute, and the critical reset_progress flag. It also adds no detail about valid values for roadmap_name or current_topic beyond naming them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('switch') and identifies several configurable targets: skill level, roadmap category, roadmap track, and topic. This is much more informative than a tautology, but it does not explicitly distinguish quick_config from siblings like set_active_roadmap or configure_voice, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling tools. It mentions switching several settings but never says 'use this instead of set_active_roadmap or configure_voice when changing multiple config values at once.' The intended usage is implied, but not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_teaching_commandRun Teaching CommandA
Execute (or dry-run) a shell command and return a full teaching card: roadmap alignment, level-appropriate What/How/Trade-offs, a Mermaid flowchart, pitfalls, curated docs, and an active-recall quiz. Errors return a Tutor Hotfix Diagnostic instead of throwing.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Working directory for execution. | |
| command | Yes | The shell command to teach and optionally run. | |
| concept | No | Concept label for the card, e.g. 'Filesystem navigation'. | |
| dry_run | No | Explain without executing. | |
| is_dangerous | No | Caller-asserted danger flag. Dangerous commands are forced into dry-run. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It usefully discloses that errors return a Tutor Hotfix Diagnostic instead of throwing, and that dry-run is possible. However, it does not mention side effects of executing commands, the behavior of the is_dangerous flag, or any safety caveats, which are important for a command-execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The main action is front-loaded and the output components are listed compactly. It is slightly long due to the enumerative output list, but every listed item adds meaningful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains what the tool returns and how errors behave, which is good for a tool with no output schema or annotations. However, it lacks guidance on safety, dry-run usage trade-offs, and how optional parameters like cwd or concept affect behavior, leaving some practical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all five parameters. The description adds no extra parameter-level detail beyond mentioning dry-run in prose, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('Execute (or dry-run) a shell command') and enumerates the full teaching card contents, making the tool's purpose unmistakable. It is clearly differentiated from siblings like verify_quiz_answer or get_next_roadmap_command, which handle different tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: whenever a shell command needs to be taught with explanation and practice materials. It does not explicitly name alternatives or state exclusions, so it stops short of a perfect score, but the context is clear enough for an agent to select it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_active_roadmapSet Active RoadmapC
Configure the active roadmap: category, roadmap name, current topic node, and progress step counters.
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes | ||
| step_index | No | ||
| total_steps | No | ||
| roadmap_name | Yes | ||
| current_topic | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing side effects. It states what is configured but does not mention that this likely changes persistent/global active state, whether prior values are overwritten, or what the result/response of the call is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with the action and resource front-loaded. Every phrase contributes meaning: the resource, the governed fields, and the counter semantics. There is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a state-setting tool with five parameters, no annotations, and no output schema, so it needs more context to be safely invoked. Missing side effects, usage timing, and clearer parameter relationships leave important gaps for an agent deciding whether and how to call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate, and it partially does by grouping step_index and total_steps as 'progress step counters' and interpreting current_topic as 'current topic node.' However, it does not explain individual parameter meaning, constraints, or how the counters relate to the roadmap state.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Configure') with a clear resource ('the active roadmap') and lists the key fields involved. This makes the tool's purpose understandable and distinguishes it from retrieval-oriented siblings like get_next_roadmap_command, though it does not explicitly name a sibling alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to choose this tool over alternatives such as quick_config or get_next_roadmap_command. There are no prerequisites, exclusions, or contextual signals explaining the intended workflow placement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_quiz_answerVerify Quiz AnswerA
Evaluate the learner's answer to the most recent active-recall quiz. Updates streak, XP and badges, and speaks feedback.
| Name | Required | Description | Default |
|---|---|---|---|
| answer | Yes | The learner's answer, either a letter (A-D) or the answer text. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the side effects: updating streak, XP, and badges, plus speaking feedback. This gives the agent a clear sense of what will change, though it does not mention reversibility or any prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise, information-dense sentence. It includes the action, target, and side effects without any filler or repetition of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no nested objects and no output schema, the description covers the essential action and effects. It could optionally mention that a quiz must be currently pending, but the phrase 'the most recent active-recall quiz' provides enough contextual framing for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the single parameter with 100% description coverage, explaining that 'answer' is either a letter (A-D) or answer text. The tool description adds no additional parameter meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Evaluate') and names the precise resource ('the learner's answer to the most recent active-recall quiz'). It also lists the tool's effects (streak, XP, badges, feedback), which clearly distinguishes it from the unrelated sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool should be used when a learner provides an answer to the most recent active-recall quiz. It does not explicitly name alternatives or exclusion conditions, but the context is clear and the sibling tools are not overlapping in function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v1.0.0- First observed
configure_voice - First observed
export_roadmap_notes - First observed
get_next_roadmap_command - First observed
get_user_stats - First observed
quick_config - First observed
run_teaching_command - First observed
set_active_roadmap - First observed
verify_quiz_answer
TDQS
Scored across 8 tools
Tools are mostly distinct, but quick_config and set_active_roadmap both handle roadmap configuration, which could cause confusion about which to use for what. Other tools like verify_quiz_answer and run_teaching_command have clear, separate purposes.
Most tools follow a verb_noun snake_case pattern (verify_quiz_answer, set_active_roadmap, get_user_stats), but 'quick_config' deviates with an adjective prefix and lacks a clear noun, breaking the pattern slightly.
Eight tools is well within the ideal range for a focused tutoring server. Each tool covers a distinct aspect of the tutor workflow—config, teaching, quiz, stats, export—with no redundancy or excessive bloat.
The tool set covers core tutor functions: configuration, teaching, assessment, progress tracking, and export. Minor gaps exist, such as no explicit tool to list available topics or manage user preferences beyond voice, but agents can work around these.
Maintenance
Related MCP Connectors
Language coaching in Codex with durable per-account memory on en-ai.ru.
Remote MCP learning coach for coding agents.
Build, version, review, and export websites, web apps, and games from a conversation.
I do everything related to coding and execution tasks
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