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L-Dopa

MCP-сервер, который помогает ИИ-агентам восстанавливаться, перефокусироваться и реально доводить дело до конца.

L-Dopa меня вылечил, ясно??

L-Dopa — это небольшой, ориентированный на продакшн сервер Model Context Protocol (MCP), который помогает агенту восстановиться, когда подход не срабатывает, контекст разрознен, а повторные попытки превращаются в цикл. Он не выполняет команды, не изменяет внешние системы и не заменяет суждение агента. Он анализирует предоставленные ему доказательства, сохраняет ограниченное состояние восстановления и предлагает более безопасный следующий шаг.

Название — шутка. Цикл восстановления — нет.

Что он делает

L-Dopa v0.1 предоставляет шесть MCP-инструментов, которые позволяют агенту диагностировать сбои, сокращать объём задачи, восстанавливать релевантный контекст и управлять повторными попытками осознанно.

Инструмент

Когда использовать

Что возвращает

diagnose

Операция завершилась сбоем, и у агента есть сообщение об ошибке или фрагмент лога.

Вероятная причина, калиброванная уверенность, отредактированные доказательства, следующие действия и рекомендации по повторным попыткам.

stimulate

Агент ходит по кругу, не делая полезных наблюдений.

Краткая перезагрузка, которая сосредотачивается на предположении и минимальной безопасной проверке.

focus

Задача слишком широкая или запутанная.

Приоритетный список из одного-пяти конкретных следующих действий; по умолчанию — три.

reuptake

Агенту нужен релевантный контекст восстановления из его сессии L-Dopa.

Компактная сводка недавних сбоев, попыток, успехов, фактов и нерешённых вопросов.

retry

Агент рассматривает или сообщает о повторной попытке.

Записанная ограниченная повторная попытка или блокировка с рекомендацией альтернативной стратегии.

fix_me

Агент застрял и хочет одну краткую последовательность восстановления.

Диагностика, сфокусированные действия, подталкивание к восстановлению и рекомендации по повторным попыткам.

Related MCP server: SentinelMCP

Принципы дизайна

Принцип

Реализация в v0.1

Без магической уверенности

Диагностическая уверенность — low, medium или high; слабые доказательства остаются слабыми.

Без слепых циклов

Повторяющиеся существенно схожие сбои, неизменённые предложения повторных попыток и лимиты повторных попыток на операцию блокируют дальнейшие повторы.

Ограниченная память

Состояние на базе JSON сохраняет только настроенное количество записей по каждой категории для каждой сессии.

Безопасно по умолчанию

L-Dopa предлагает только диагностику и планирование. Он никогда не выполняет shell-команды или внешние действия.

Вывод с учётом учётных данных

Распространённые шаблоны токенов, заголовков авторизации, паролей, API-ключей, JWT, AWS-ключей и GitHub-токенов редактируются до попадания в состояние, логи и вывод инструментов.

Простое развёртывание

Сервер использует стандартный MCP stdio-транспорт и требует Node.js 18 или новее.

Установка

Клонируйте репозиторий и установите зависимости:

git clone https://github.com/mshanghai570/L-Dopa.git
cd L-Dopa
npm install
npm run build

Запустите stdio-сервер вручную:

npm start

npm start намеренно ожидает ввода. MCP-серверы общаются через JSON-RPC по стандартному вводу и выводу, поэтому обычно клиент MCP запускает его за вас.

Подключение MCP-клиента

Сначала соберите L-Dopa, затем используйте его исполняемую точку входа. Следующая универсальная конфигурация MCP совместима с клиентами, поддерживающими локальные stdio-серверы:

{
  "mcpServers": {
    "l-dopa": {
      "command": "node",
      "args": ["/absolute/path/to/L-Dopa/dist/index.js"],
      "env": {
        "LDOPA_STATE_FILE": "/absolute/path/to/l-dopa-state.json",
        "LDOPA_MAX_HISTORY": "50",
        "LDOPA_RETRY_LIMIT": "3",
        "LDOPA_LOG_LEVEL": "info"
      }
    }
  }
}

Для установленного пакета команда может быть l-dopa, в зависимости от окружения клиента. Держите стандартный вывод зарезервированным для сообщений протокола MCP. L-Dopa записывает собственные краткие структурированные операционные логи в стандартный поток ошибок.

Конфигурация

L-Dopa работает с безопасными значениями по умолчанию и может быть настроен через JSON-файл и/или переменные окружения. Скопируйте предоставленный пример, чтобы начать:

cp l-dopa.config.example.json l-dopa.config.json
LDOPA_CONFIG=./l-dopa.config.json npm start

Переменные окружения переопределяют значения из файла.

Настройка

JSON-свойство

Переменная окружения

По умолчанию

Значение

Путь к состоянию

stateFile

LDOPA_STATE_FILE

~/.l-dopa/state.json

Расположение ограниченного JSON-хранилища сессий.

Лимит истории

maxHistory

LDOPA_MAX_HISTORY

50

Положительное максимальное количество записей, сохраняемых для каждой категории в сессии.

Лимит повторных попыток

retryLimit

LDOPA_RETRY_LIMIT

3

Положительное максимальное количество запланированных/зарегистрированных повторных попыток для операции, после которого новые повторы блокируются.

Уровень логирования

logLevel

LDOPA_LOG_LEVEL

info

Одно из значений: debug, info, warn или error.

Файл конфигурации

—

LDOPA_CONFIG

—

Необязательный путь к JSON-файлу конфигурации.

Конфигурация не содержит настроек учётных данных провайдера, потому что эта версия не совершает вызовов к моделям или провайдерам. Если будущему расширению потребуются учётные данные, передавайте их через переменные окружения; не добавляйте их в репозиторий, файл конфигурации или промпт восстановления.

Справочник инструментов

Все текстовые аргументы ограничиваются по длине и очищаются от учётных данных до того, как L-Dopa сохраняет или возвращает их. sessionId по умолчанию равен "default", но агентам следует использовать стабильный ID для каждой задачи или разговора, чтобы предотвратить смешивание несвязанных историй восстановления.

diagnose

Используйте diagnose после сбоя, предоставив столько полезного контекста, сколько доступно. errorMessage, recentOperation, logs, attemptedSolution, expectedResult и actualResult необязательны, но точная ошибка или фактический результат делают ответ более полезным.

{
  "sessionId": "deploy-2026-08-27",
  "recentOperation": "Deploy version 0.1.0",
  "errorMessage": "429 Too Many Requests",
  "attemptedSolution": "Immediately retried the deployment",
  "expectedResult": "Deployment accepted",
  "actualResult": "The API rejected the request"
}

Ответ включает likelyCause, confidence, evidence, recommendedNextActions, retryAppropriate, tryDifferentStrategy и индикатор redacted. Обнаружение намеренно эвристическое, а не ложная категоричность.

stimulate

Используйте stimulate, когда агенту нужно перестать комментировать и начать учиться. Передайте обязательный task и необязательный context с высокой информативностью.

{
  "sessionId": "deploy-2026-08-27",
  "task": "Repair the deployment",
  "context": "The health check timed out twice after a successful build"
}

Стратегия восстановления делает акцент на минимальном проверяемом действии и предостерегает от неизменных циклов.

focus

Используйте focus, чтобы превратить широкую задачу в намеренно короткую последовательность. maxSteps необязателен и принимает значения от одного до пяти; по умолчанию он равен трём.

{
  "sessionId": "deploy-2026-08-27",
  "task": "Repair the deployment and verify availability",
  "context": "Health checks time out",
  "maxSteps": 3
}

reuptake

Используйте reuptake, когда агенту нужен релевантный контекст сессии без выгрузки полного транскрипта. limit по умолчанию равен пяти и ограничен двадцатью.

{
  "sessionId": "deploy-2026-08-27",
  "limit": 5
}

Он возвращает текущую задачу, статус восстановления, недавние сбои, опробованные решения, успешные подходы, обнаруженные факты, нерешённые вопросы и количество повторных попыток. Инструменты v0.1 пока не предоставляют отдельного инструмента для записи фактов; discoveredFacts зарезервирован для расширений и остаётся в компактной схеме.

retry

Используйте retry, чтобы создать явную запись о повторной попытке или сообщить о её результате. proposedChange должен указывать, что именно изменилось. L-Dopa допускает записи о запланированных, успешных и неудачных повторах, но сам никогда не выполняет повторную попытку.

{
  "sessionId": "deploy-2026-08-27",
  "operation": "Deploy version 0.1.0",
  "previousFailure": "429 Too Many Requests",
  "proposedChange": "Wait for Retry-After and submit only one request",
  "result": "planned"
}

L-Dopa блокирует повторную попытку, если исчерпан настроенный лимит операции, повторился тот же сбой или существующая повторная попытка повторяется без изменённого предложения. Его ответ о блокировке рекомендует ограниченный альтернативный путь, который может включать передачу чётко очерченной подзадачи и собранных доказательств другому способному агенту.

fix_me

Используйте fix_me как краткую версию последовательности diagnose → focus → stimulate → retry guidance. Он записывает переданный сбой, если он есть, а затем возвращает план; он не выполняет его.

{
  "sessionId": "publish-0.1.0",
  "task": "Publish the package safely",
  "recentOperation": "npm publish",
  "errorMessage": "401 Unauthorized",
  "attemptedSolution": "Re-ran the same command"
}

Состояние и конфиденциальность

Хранилище состояния — это обычный JSON-файл, записываемый атомарно с режимом 0600. Оно имеет версионированную структуру и хранит отдельные сессии по ключу sessionId. В пределах каждой сессии записи о сбоях, повторных попытках, опробованных решениях, успешных подходах и обнаруженных фактах сокращаются до maxHistory.

Состояние намеренно лёгкое, а не система долговременной памяти. Оно находится локально на машине текущего пользователя и не передаётся L-Dopa. Просматривайте или удаляйте настроенный файл состояния всякий раз, когда нужно очистить историю восстановления.

Важно: Редактирование охватывает несколько распространённых шаблонов учётных данных, но это защитная мера, а не разрешение отправлять секреты. Не помещайте намеренно пароли, токены, приватные ключи или полные заголовки авторизации в диагностический ввод.

Разработка

npm install
npm run build
npm test

Проект намеренно модульный:

src/
  config.ts       Configuration loading and validation
  index.ts        Executable stdio MCP entry point
  logger.ts       Structured, redacted standard-error logging
  redaction.ts    Credential-detection and output redaction
  recovery.ts     Diagnostic, focus, stimulation, and plan logic
  server.ts       MCP server and tool registrations
  state.ts        Bounded, atomic JSON session storage
  types.ts        Shared contracts
tests/
  l-dopa.test.ts  End-to-end MCP and state behavior tests

Тестовое покрытие

Автоматизированный набор тестов подключает реальный клиент и сервер MCP через транспорт в памяти SDK. Он покрывает инициализацию сервера, обнаружение MCP-инструментов, каждый инструмент, сохранение состояния, ограниченное хранение, лимиты повторных попыток, неизменные повторы, обнаружение повторяющихся сбоев и редактирование учётных данных.

Запустите его с помощью:

npm test

Ограничения и дорожная карта

L-Dopa v0.1 использует детерминированные эвристики, поэтому распознаёт распространённые классы сбоев, но не является всезнающим отладчиком. В нём намеренно нет векторного хранилища, удалённого сохранения, интеграции с провайдерами моделей и возможности выполнения команд. Он не анализирует скрытую цепочку рассуждений агента; он работает только с предоставленным операционным контекстом.

Будущие дополнения должны сохранять эти границы: добавляйте инструмент только тогда, когда он даёт явную пользу для восстановления; держите выполнение команд в отдельном компоненте с контролем разрешений; сохраняйте состояние ограниченным и проверяемым.

Лицензия

MIT

Available Tools

6 tools
diagnoseDiagnose a failureA

Analyze an error or failed operation, record it in bounded session state, and recommend safe next actions.

NameRequiredDescriptionDefault
logsNoRelevant log excerpt. Credentials are redacted.
sessionIdNoA stable identifier for this agent recovery session.default
actualResultNoWhat happened instead.
errorMessageNoThe exact error message, if available.
expectedResultNoWhat should have happened.
recentOperationNoThe operation that most recently failed.
attemptedSolutionNoA solution already attempted.

TDQS

A3.8/5.0
Behavior4/5

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

With annotations providing only broad flags, the description adds meaningful behavioral detail: it records state in a bounded session and recommends rather than executes actions. This clarifies side effects and scope without contradicting the annotations.

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, tightly worded sentence front-loads the core verb and object, then packs in two meaningful behavioral outcomes. There is no filler or redundancy.

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 tool with seven optional but fully documented parameters and no output schema, the description conveys the essential flow: analyze, record, and recommend. It stops short of describing the exact shape of the recommendation output, but it is sufficiently complete for an agent to understand the tool's role.

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%, and the input schema already documents each parameter, so the tool description does not need to repeat parameter details. The description adds no parameter-specific meaning beyond the schema, 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Analyze') and resource ('an error or failed operation'), and adds two concrete outcomes: recording in bounded session state and recommending safe next actions. It is clear about what the tool does, though it does not explicitly differentiate it from sibling tools like retry or fix_me.

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 phrase 'Analyze an error or failed operation' implies the intended trigger, and 'recommend safe next actions' positions it as an advisory step before acting. However, it gives no explicit guidance on when not to use it or how it compares to sibling alternatives.

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

fix_meCreate a complete recovery sequenceA

Combine diagnosis, focus, stimulation, and retry guidance into a concise recovery plan without executing commands.

NameRequiredDescriptionDefault
logsNoRelevant log excerpt. Credentials are redacted.
taskYesThe task that is stuck or needs recovery.
sessionIdNoA stable identifier for this agent recovery session.default
actualResultNoActual result.
errorMessageNoThe exact error message, if available.
expectedResultNoExpected result.
recentOperationNoThe operation that failed.
attemptedSolutionNoA solution already tried.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already tell the agent the operation is not read-only, not idempotent, and not destructive. The description adds valuable behavioral context beyond those annotations by explicitly stating that no commands are executed, meaning the tool only produces guidance/planning content. This helps the agent set expectations about 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It states the action, the inputs, the output, and a key behavioral constraint ('without executing commands') in under 15 words. Every phrase earns its place.

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 8-parameter schema with full coverage, annotations, and no output schema, the description provides enough context: it defines the output as a concise recovery plan and clarifies the non-execution behavior. It does not detail the plan's format or how to handle partially supplied inputs, but the required task parameter and well-described optional parameters make the tool usable.

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 coverage is 100%, so all eight parameters already have descriptions. The tool description adds conceptual meaning by mapping the plan components to diagnosis, focus, stimulation, and retry guidance, but it does not explain how specific parameters map to those components. Baseline 3 is appropriate because the schema carries the parameter-documentation burden.

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 uses a specific verb ('Combine') and resource ('diagnosis, focus, stimulation, and retry guidance into a concise recovery plan'), so an agent knows what the tool produces. It also distinguishes itself from the sibling tools diagnose, focus, stimulate, and retry by framing those as components rather than the tool's own action. The phrase 'without executing commands' further differentiates it from the more action-oriented siblings.

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 clearly conveys that this tool is for synthesizing a recovery plan rather than executing recovery actions, which gives the agent a clear decision context. It does not explicitly enumerate exclusions or say 'use X when...', but naming the component tools implies when this orchestrator is appropriate.

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

focusFocus the next actionsA

Reduce a complicated task to a short, prioritized sequence of concrete, verifiable next actions.

NameRequiredDescriptionDefault
taskYesThe task to reduce into next actions.
contextNoRelevant blocker, constraint, or diagnostic finding.
maxStepsNoNumber of actions to return; defaults to three.
sessionIdNoA stable identifier for this agent recovery session.default

TDQS

A3.5/5.0
Behavior3/5

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

Annotations provide no positive behavioral hints (all false), so the description itself must convey behavior. It does state the transformation and output nature, but it does not disclose aspects like whether actions are executed, how sessions affect behavior, or any side effects. This is adequate but not richly transparent.

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, front-loaded sentence with no wasted words. It efficiently conveys the core purpose and expected output without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does indicate the return shape ('sequence of concrete, verifiable next actions'), which helps. However, it lacks guidance on how the tool relates to the provided sessionId/context and does not address when it should be preferred over sibling tools, leaving some practical gaps.

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%, so the input schema fully documents all four parameters. The description adds no parameter-specific meaning beyond the schema, hitting the baseline expected when the schema carries the load.

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?

The description names a specific verb ('reduce') and resource ('a complicated task') and states the output: 'a short, prioritized sequence of concrete, verifiable next actions.' This clearly communicates the tool's purpose, though it does not explicitly contrast it with siblings like diagnose or retry.

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 implies the tool should be used when a task is complicated and needs to be broken into manageable next actions. However, it gives no explicit when-to-use vs. alternative guidance and does not mention any exclusions or sibling tools.

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

retryPlan or record an intelligent retryA

Record a bounded retry with its specific change and result. Blocks unchanged or exhausted retry loops.

NameRequiredDescriptionDefault
notesNoShort result or verification note.
resultNoWhether the retry is planned, succeeded, or failed.planned
operationYesThe operation to retry.
sessionIdNoA stable identifier for this agent recovery session.default
proposedChangeNoWhat will be changed before retrying.
previousFailureNoThe previous failure for this operation.

TDQS

A3.9/5.0
Behavior4/5

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

Annotations only say the tool is not read-only, not idempotent, and not destructive. The description adds a real behavioral trait beyond those annotations: retries must be bounded, and unchanged or exhausted retry loops are blocked. This gives the agent useful expectations about side effects and constraints, with no contradiction against the annotations.

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?

Two sentences with no filler: the first states the core action and required components, the second states the key constraint. It is front-loaded and every phrase earns its place. The description is appropriately sized for what it conveys.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema covers all parameters well and the description gives the core retry constraint, so the tool is basically usable. However, the title mentions 'Plan or record' while the description only explains recording, and there is no output schema or description of what happens when a retry is blocked or succeeds. The exact meaning of 'bounded' and the return behavior remain under-specified.

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%, and each parameter already has a meaningful description, so the baseline is 3. The description only echoes 'change and result' which maps to proposedChange/result, and it does not add operational detail about sessionId, previousFailure, or notes. It does not need to compensate for missing schema docs.

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?

States a specific action and resource: 'Record a bounded retry with its specific change and result.' It also adds the distinguishing guardrail—'Blocks unchanged or exhausted retry loops'—which separates it from sibling tools like diagnose or fix_me. The title's 'Plan or record' is somewhat broader, but the description still gives a clear, non-tautological purpose.

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 implies this is for retrying an operation after a change and warns against unchanged or exhausted retry loops, so there is some embedded when-not guidance. However, it never explicitly states the triggering conditions for using this tool over a sibling, nor does it name alternatives. The usage context remains mostly inferred rather than directly stated.

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

reuptakeRecover relevant session contextB
Read-onlyIdempotent

Retrieve a compact, relevant summary of failures, attempts, facts, successes, and unresolved issues from this session.

NameRequiredDescriptionDefault
limitNoMaximum recent entries per context category.
sessionIdNoA stable identifier for this agent recovery session.default

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds useful output composition details (failures, attempts, facts, successes, unresolved issues) but does not disclose additional behavioral traits such as staleness, scoping caveats, or return formatting.

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?

One front-loaded sentence states the action, the resource, and the scope with no wasted words. It is appropriately sized for the tool's simplicity.

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, side-effect-free retrieval tool with fully documented parameters, the description gives an agent enough to call it and understand the returned content. It could briefly mention when to use it relative to siblings, but the essential invocation context is present.

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 fully documents limit and sessionId with defaults, bounds, and descriptions, so schema coverage is 100%. The description adds no parameter-specific meaning or usage examples, keeping this at the baseline.

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?

The description uses a specific verb ('Retrieve') and clearly identifies the resource: a compact session summary containing failures, attempts, facts, successes, and unresolved issues. It is unambiguous about what the tool does, though it does not explicitly contrast with sibling tools like diagnose or focus.

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?

There is no guidance on when to use reuptake versus its siblings such as diagnose, focus, or fix_me. The intended use case is only implied by the title and description, not explicitly stated as a condition or recommendation.

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

stimulateNudge a stuck agentA

Return a concise, structured recovery nudge that emphasizes reassessment, minimal checks, and changed approaches.

NameRequiredDescriptionDefault
taskYesThe task on which the agent is stuck.
contextNoThe most relevant constraint, failed assumption, or observation.
sessionIdNoA stable identifier for this agent recovery session.default

TDQS

A3.7/5.0
Behavior4/5

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

The description is transparent about the primary behavior: it returns a nudge rather than performing the task, and it specifies the nudge's 'concise, structured' form and themes. With no output schema and annotations that provide no positive safety signal, this is meaningful disclosure, though side effects and session-state behavior are not addressed.

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 sentence that front-loads the action ('Return'), the deliverable ('recovery nudge'), and the key content directives. Every phrase earns its place, with no filler or duplicated schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The definition is adequate for a simple text-generation tool with fully documented parameters and a clear title. However, it lacks explicit sibling differentiation, usage timing, and an output-format preview, so an agent choosing among the six siblings gets only partial context.

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%, with clear descriptions for task, context, and sessionId, so the baseline of 3 applies. The description's mention of reassessment and changed approaches hints at how context might be used but adds no concrete parameter-level meaning beyond the schema.

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?

The description names a specific deliverable—a 'concise, structured recovery nudge'—and defines its content emphasis (reassessment, minimal checks, changed approaches), so an agent knows what the tool produces. It does not explicitly distinguish this from sibling tools like diagnose or retry, so it falls 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.

Usage Guidelines3/5

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

Usage context is implied rather than stated: the title and the task parameter describe an agent that is stuck, and context mentions failed assumptions. However, the description never says when to prefer stimulate over diagnose, reuptake, focus, retry, or fix_me, nor does it offer exclusion conditions.

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.

  1. 6 tool updatesv0.1.0
    • First observeddiagnose
    • First observedfix_me
    • First observedfocus
    • First observedretry
    • First observedreuptake
    • First observedstimulate

TDQS

A3.6/5.0

Scored across 6 tools

Disambiguation2/5

Several tools have unclear boundaries: diagnose, focus, and fix_me all produce recommended next actions or plans, while stimulate and focus both generate recovery-oriented output. Only reuptake and retry are clearly distinct, making tool selection genuinely ambiguous.

Naming Consistency4/5

The tools mostly follow a consistent lowercase imperative-verb style: diagnose, stimulate, focus, retry. The main deviation is fix_me, which introduces an underscore and an object pronoun, but the overall naming pattern is still recognizable.

Tool Count4/5

Six tools is a reasonable size for a session-recovery-focused server. However, fix_me is an aggregate of other tools and adds some redundancy, so the set is slightly less lean than it could be.

Completeness4/5

The tool surface covers the core recovery loop well: diagnose failures, focus on next actions, retry with bounded state, and retrieve session context. Minor gaps exist around explicit session reset or state-clearing operations, but agents can generally work around them.

Maintenance

ActivityStale
ResponsivenessNo issues

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