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DeckProbe MCP Server

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DeckProbe MCP Server

Позвольте агенту узнать, что внутри PDF, Office или iWork файла — не открывая его.

CI npm License: MIT

Установка · Инструменты · Конфигурация · Безопасность · Как это работает · DeckProbe

MCP-сервер, который предоставляет DeckProbeffprobe для документов — в виде четырех типизированных инструментов. Запрашивайте количество страниц, слайдов, метаданные, сигналы шифрования и макросов, структуру или целостность и получайте ограниченный, детерминированный JSON с уверенностью, доказательствами и измеренной стоимостью ввода-вывода.

Ничего не рендерится, макросы не выполняются, внешние ссылки не открываются, сетевые соединения не устанавливаются. Это безопасно для работы с ненадежными файлами.

// probe { "path": "deck.pptx", "targets": ["slide_count"], "view": "values" }
{
  "schema_version": 2,
  "status": "ok",
  "driver": { "id": "powerpoint", "profile": "pptx" },
  "values": { "powerpoint.slide_count": 31 },
  "view": "values"
}

Установка

Заранее ничего устанавливать не нужно — npx загружает сервер и движок вместе.

Claude Code

claude mcp add deckprobe -- npx -y @deckflow/deckprobe-mcp

Claude Desktop, Cursor, VS Code, Zed и всё остальное, что читает mcpServers

{
  "mcpServers": {
    "deckprobe": {
      "command": "npx",
      "args": ["-y", "@deckflow/deckprobe-mcp"]
    }
  }
}

Для фиксированной установки используйте npm install -g @deckflow/deckprobe-mcp и команду deckprobe-mcp.

Требуется Node.js 20 или новее. Двоичный файл движка поставляется как опциональная зависимость для каждой платформы: macOS, Linux (glibc и musl) и Windows на x86-64 и ARM64; в остальных случаях сервер использует тот же движок, скомпилированный в WebAssembly, так что npx работает везде, где работает Node.

Related MCP server: flexorch-mcp

Инструменты

Инструмент

Для чего используется

probe

Всё об одном документе

probe_batch

Инвентаризация или сортировка многих документов одним вызовом

list_formats

Какие форматы поддерживаются и где заканчивается поддержка

list_targets

Точные имена целей, которые предлагает формат

Также есть один ресурс, deckprobe://schema, содержащий JSON-схему отчёта, встроенную в работающий движок.

probe

{
  "path": "reports/q3.pptx",
  "targets": ["@summary", "@security"],  // presets, short names, or canonical names
  "level": "metadata",                   // header | metadata | deep
  "min_confidence": "high",              // low | medium | high | exact
  "target_confidence": { "slide_count": "exact" },
  "view": "report",                      // report | values
  "budget": { "max_physical_bytes": 8388608, "timeout_ms": 1000 }
}

targets принимает короткие имена (slide_count), канонические имена (powerpoint.slide_count) и пресеты:

Пресет

Расшифровка

@header

Только идентичность контейнера — формат, размер, соответствие расширения, флаг шифрования

@summary

Идентичность, общие метаданные и основная структура

@security

Шифрование, макросы, подписи, внешние ссылки, активное содержимое

@structure

Счётчики, имена и размеры, принадлежащие формату

@assets

Изображения, медиа, превью, шрифты, встроенные объекты

@quality

Целостность, восстановление, соответствие расширения, конформность

@format

Все цели, специфичные для формата, на активном уровне

@all

Всё доступное на активном уровне

@summary намеренно опускает статистику, требующую полного чтения файла. page_count для PDF — яркий пример; запрашивайте его явно.

probe_batch

{ "paths": ["a.pdf", "b.pptx", "c.xlsx"], "targets": ["@security"] }

Один процесс движка обрабатывает весь пакет. Результаты возвращаются в порядке ввода, каждый со своим отчётом или своей ошибкой, так что один плохой файл не испортит весь запуск. По умолчанию используется компактное представление values. Только буквальные пути — раскрывайте glob-шаблоны самостоятельно.

list_formats и list_targets

list_targets принимает format (pdf, docx, xlsx, pptx, doc, xls, ppt, key, numbers, pages) и возвращает для каждой цели её псевдонимы, описание, тип значения, минимальный уровень, класс стоимости и принадлежность к селектору. Передайте detail: "full" для полного отчёта движка, включая фрагменты JSON-схемы для каждой цели и расширенные списки селекторов.

Оба кэшируются на время жизни процесса сервера.

Чтение отчёта

Результат инструмента — это собственная оболочка schema-v2 движка, без изменений. Два момента стоит знать перед её использованием:

  • status: "partial" — это не ошибка. Это означает, что по крайней мере одна запрошенная цель не может быть разрешена с запрошенной уверенностью. Она указана в execution.unresolved_targets, и все остальные результаты остаются в силе.

  • confidence_score — это фиксированная константа для каждой метки (0.4, 0.7, 0.95, 1.0), а не калиброванная вероятность. 0.95 не означает, что значение верно в 95% случаев.

Только результаты со статусом resolved или estimated содержат value. unknown встречается часто и обычно означает, что документ просто не фиксирует этот факт.

Неудачный вызов возвращает isError с оболочкой ошибки движка и одной строкой, объясняющей, что делать. Ошибки, которые сам сервер вызывает до запуска движка — отсутствующий путь, каталог, путь вне списка разрешений, превышение срока — используют ту же форму оболочки с кодом с префиксом MCP_ и origin: "mcp-server".

Конфигурация

Каждый параметр — это переменная окружения, задаваемая в конфигурации MCP вашего клиента. Все они необязательны.

Переменная

По умолчанию

Значение

DECKPROBE_MCP_BIN

Двоичный файл движка для использования вместо встроенного

DECKPROBE_MCP_ROOTS

без ограничений

Разрешённые каталоги, разделённые как PATH

DECKPROBE_MCP_TIMEOUT_MS

30000

Жёсткий срок выполнения каждого вызова для процесса движка

DECKPROBE_MCP_MAX_CONCURRENCY

4

Одновременные процессы движка

DECKPROBE_MCP_MAX_BATCH

64

Пути, принимаемые одним вызовом probe_batch

{
  "deckprobe": {
    "command": "npx",
    "args": ["-y", "@deckflow/deckprobe-mcp"],
    "env": { "DECKPROBE_MCP_ROOTS": "/Users/me/Documents:/Users/me/Downloads" }
  }
}

Безопасность

DeckProbe создан для ненадёжного ввода: ограниченный разбор, отсутствие рендерера, интерпретатора макросов, разрешения внешних ссылок и сетевого доступа. Этот сервер добавляет два дополнительных аспекта.

  • Изоляция процессов и жёсткий срок. Каждый проб выполняется в собственном короткоживущем процессе, который завершается, если превышает DECKPROBE_MCP_TIMEOUT_MS.

  • Необязательный список разрешений на чтение. DECKPROBE_MCP_ROOTS ограничивает доступное дерево; пути разрешаются через симлинки перед проверкой, поэтому ссылка не может обойти его. По умолчанию доступ не ограничен, что соответствует CLI, который пользователь мог бы запустить сам — установите его для общих или автоматизированных развёртываний.

Отчёты описывают документ (метаданные, счётчики, сигналы), а не воспроизводят его содержимое. Обратите внимание, что значения отчёта, такие как заголовок документа, по-прежнему являются строками, контролируемыми атакующим: сервер передаёт их как JSON-данные и никогда не интерполирует их в инструкции, и потребитель должен относиться к ним так же.

Сообщите об уязвимости конфиденциально, как описано в SECURITY.md.

Как это работает

MCP client
    │  JSON-RPC over stdio
    ▼
deckprobe-mcp ── validates arguments, resolves the path, maps the result
    │  argv + stdout (one process per probe, or one --jsonl process per batch)
    ▼
DeckProbe engine ── plans the cheapest paths that answer the request

Сервер запускает нативный CLI DeckProbe, а не вызывает WebAssembly-сборку. CLI читает только те диапазоны байтов, которые нужны плану проб, тогда как WebAssembly-путь держит весь файл в памяти, а отдельный процесс ОС как изолирует ненадёжный разбор, так и может быть полностью завершён. Движок выбирается в следующем порядке:

  1. DECKPROBE_MCP_BIN

  2. двоичный файл, поставляемый с зависимостью @deckflow/deckprobe этого пакета

  3. deckprobe в PATH

  4. встроенный WebAssembly-движок

Выбранный движок записывается в stderr при запуске. stdout принадлежит транспорту MCP и больше ничего не несёт.

MCP-сервер или навык агента?

DeckProbe также поставляется с Agent Skill, который обучает агента с доступом к оболочке использовать CLI напрямую. Оба обучают одному и тому же словарю. Используйте навык, когда у агента есть оболочка и вам нужна полная поверхность CLI; используйте этот сервер, когда её нет или когда вы хотите, чтобы типизированные аргументы проверялись до запуска движка.

Разработка

npm install
npm test          # typecheck, lint, build, and the full suite
npm run test:watch

Вклад приветствуется — см. CONTRIBUTING.md. Обоснование дизайна, включая отклонённые альтернативы, находится в docs/rfc.md.

Лицензия

MIT. См. LICENSE.

Available Tools

4 tools
list_formatsList supported formatsA
Read-onlyIdempotent

List the document formats DeckProbe can inspect: drivers, the extensions each one handles, and where support stops. Call this when you are unsure whether a file type is supported at all.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context about the exact output content (drivers, extensions, support limitations), which goes beyond the annotations. No contradictions with 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?

The description is two sentences, with the primary purpose and scope front-loaded. It avoids redundancy and every sentence earns its place—the first states what it lists, the second when to call it. No unnecessary detail.

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?

For a simple, parameterless list tool with no output schema, the description fully explains what the tool returns (drivers, extensions, and support limits). There is nothing missing for an agent to correctly invoke it and interpret the result. Complexity is low, so this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema is fully covered (100% by default). There is nothing to add about parameters; the description doesn't need to explain any. The baseline for zero parameters is 4, and no additional info is required.

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 states a specific verb ('List'), a clear resource ('document formats DeckProbe can inspect'), and specifies the content (drivers, extensions, and where support stops). It effectively distinguishes itself from sibling tools like probe and list_targets by focusing on format capabilities rather than probing or target listing.

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 gives explicit when-to-use guidance: 'Call this when you are unsure whether a file type is supported at all.' It doesn't mention alternatives, but the trigger condition is clear and implies that if you have a specific file, you would use probe instead. It could be improved by naming the sibling tools explicitly, but the guidance is sufficient.

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

list_targetsList targets for a formatA
Read-onlyIdempotent

List every target a format supports, with its aliases, value type, minimum probe level, cost class, and which @selectors include it. Call this before naming a target you have not already seen — probe rejects an unknown one rather than guessing.

ParametersJSON Schema
NameRequiredDescriptionDefault
detailNocompact (default): target names, aliases, descriptions, levels, and selector membership. full: the complete report, including each target's JSON Schema fragment and every selector's expanded member list.
formatYesA format profile from list_formats, such as "pdf", "docx", "xlsx", "pptx", "doc", "xls", "ppt", "key", "numbers", or "pages".

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, covering safety. The description adds behavioral context by spelling out returned fields and the probe rejection behavior, which matters for planning calls. No contradictions.

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 front-load the core purpose and output contents, then give one practical usage rule. No filler or repetition of schema details.

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 a rich annotation set, fully documented parameters, and a description that names the output fields and the prerequisite call, an agent has enough to invoke the tool correctly even with no output schema.

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 the schema already explains format and detail fully, including enumerations and examples. The description adds no new parameter-level semantics beyond naming the report contents, so baseline 3 is appropriate.

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 states a specific verb (list) and resource (targets for a given format), enumerates exactly what is included (aliases, value type, minimum probe level, cost class, selector membership), and contrasts with probe by stating probe rejects unknown targets. This distinguishes it from sibling tools list_formats and probe.

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?

It explicitly instructs when to call: before naming a target not already seen, because probe rejects unknowns rather than guessing. It also ties the format parameter to list_formats, implying the prerequisite and differentiating from list_formats.

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

probeProbe a documentA
Read-onlyIdempotent

Read facts about one local PDF, Microsoft Office, or Apple iWork document without opening or rendering it: page, slide, and sheet counts; title, author, and dates; encryption, macro, signature, and active-content signals; structure; embedded assets; and integrity. Handles .pdf, .docx/.xlsx/.pptx, legacy .doc/.xls/.ppt, and modern .key/.numbers/.pages.

Start with targets ["@summary"], or ["@security"] to triage an untrusted file. Prefer this over unzipping the document or parsing its bytes by hand.

Reports facts ABOUT the document, never its text: it does not extract, render, run macros, follow external references, or open a network connection.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesPath to the document. The filename extension selects the format driver, and the container is then verified against it.
viewNoreport: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map.
levelNoProbe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so.
budgetNoOverride the level's resource limits. Raise after a BUDGET_EXCEEDED error.
targetsNoShort names (slide_count), canonical names (powerpoint.slide_count), or presets: @header, @summary, @security, @structure, @assets, @quality, @format, @all. Defaults to the driver's own set. Call list_targets rather than guessing a name. @summary omits statistics needing a full-file read, so ask for a PDF's page_count explicitly.
min_confidenceNoWeakest evidence a path may offer. Default high; lower it to accept an approximation.
target_confidenceNoPer-target override, e.g. {"slide_count": "exact"} to force the authoritative path.

Output Schema

ParametersJSON Schema
NameRequiredDescription
statusNo
schema_versionNo

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds critical behavioral context beyond those hints: it does not extract, render, run macros, follow external references, or open a network connection; it handles legacy formats; it can hit resource limits (referenced by 'Raise after a BUDGET_EXCEEDED error'). This is exactly the kind of non-obvious behavior an agent needs to trust the tool with untrusted files.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured: opening scope sentence, format list, usage hint, and a final 'does not' sentence. It is front-loaded with the core purpose and scoping. It earns its sentences; only a minor redundancy exists (the 'Prefer this over...' sentence partially repeats the 'does not' list). Not a 5, but far above the typical terse definition.

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 7 parameters, nested budget object, output schema present, and complex behavior (format drivers, confidence levels, presets, resource limits), the description provides substantial orientation: preset suggestions, the @summary caveat, the budget-error hint, and a clear non-extraction guarantee. The description does not explain what each target means, but it correctly defers to list_targets. So it's complete enough without being exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 7 parameters well. The description adds important cross-references that the schema alone does not capture: the distinction between @summary and full-read statistics, the warning that @summary omits page_count so ask explicitly, and that list_targets should be used rather than guessing names. This goes beyond a baseline 3 by explaining how the parameters interact with presets and the driver's default set.

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 a specific verb ('Read facts about one local PDF, Microsoft Office, or Apple iWork document') plus a precise resource list (page/slide/sheet counts, title/author/dates, encryption, macros, structure, assets, integrity). The scope is explicit: it reports facts ABOUT the document, never extracts text, renders, runs macros, or opens connections. It also names sibling tools (list_targets, probe_batch) and distinguishes from unzipping/byte-parsing by hand. This is clear and differentiated.

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?

The description explicitly advises 'Start with targets ["@summary"], or ["@security"] to triage an untrusted file.' and 'Prefer this over unzipping the document or parsing its bytes by hand.' It also warns about @summary omitting statistics and instructs to 'Call list_targets rather than guessing a name.' This provides direct when-to-use and when-not-to-use guidance, plus pointers to alternatives.

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

probe_batchProbe several documentsA
Read-onlyIdempotent

Probe many local documents in one call — inventory a folder, triage a batch of uploads, or compare a set of files. One engine process handles the whole batch, so this is much cheaper than calling probe once per file.

Takes literal paths; expand any glob yourself first. Returns one entry per path, in the order given, each carrying that file's report or its own error envelope. A file that fails does not affect the others.

Defaults to the compact "values" view because inventory rarely needs per-target evidence; pass view: "report" when it does.

ParametersJSON Schema
NameRequiredDescriptionDefault
viewNoreport: full evidence — value, confidence, path, and cost per target. values: a compact target-to-value map.
levelNoProbe budget and eligible paths. header: identity only. metadata (default). deep: higher-cost paths, needed only when a target's min_level says so.
pathsYesDocument paths, at most 64 per call. Literal paths only.
budgetNoOverride the level's resource limits. Raise after a BUDGET_EXCEEDED error.
targetsNoShort names (slide_count), canonical names (powerpoint.slide_count), or presets: @header, @summary, @security, @structure, @assets, @quality, @format, @all. Defaults to the driver's own set. Call list_targets rather than guessing a name. @summary omits statistics needing a full-file read, so ask for a PDF's page_count explicitly.
min_confidenceNoWeakest evidence a path may offer. Default high; lower it to accept an approximation.

Output Schema

ParametersJSON Schema
NameRequiredDescription
reportsYesOne entry per requested path, in order. A per-file failure is confined to it.

TDQS

A4.8/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: one engine process for the batch, per-path results in order, error envelopes per file, failure isolation, default view and when to switch. Annotations already cover read-only/idempotent/destructive, and the description does not contradict them.

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?

Three sentences, zero fluff. The first sentence front-loads purpose and use cases; the second covers path handling and return behavior; the third gives view guidance. Every sentence 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?

For a tool with 6 parameters, nested objects, and a full output schema, the description covers the essential usage context: batch behavior, order of results, error isolation, and view default. It does not mention budget override or target selection, but those are adequately documented in the schema. The description is sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds valuable semantic guidance: 'Takes literal paths; expand any glob yourself first' clarifies the paths parameter, and the view default rationale ('inventory rarely needs per-target evidence') adds context beyond the schema. It does not elaborate on every parameter, but the key ones receive useful extra meaning.

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 probes many local documents in one call, listing concrete use cases (inventory a folder, triage a batch, compare files). It distinguishes itself from the sibling 'probe' by explicitly being the batch counterpart.

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?

The description explicitly explains when to use this tool ('Probe many local documents in one call'), gives practical scenarios, and contrasts cost efficiency ('much cheaper than calling probe once per file'). It also gives guidance on view selection ('pass view: report when it does').

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. Dates show when Glama detected each change.

  1. 4 tool updatesv0.1.1
    • First observedlist_formats
    • First observedlist_targets
    • First observedprobe
    • First observedprobe_batch

TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a wholly distinct purpose: probe handles a single file, probe_batch handles multiples, list_formats enumerates supported file types, and list_targets enumerates probe targets. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tools follow a consistent lowercase_snake_case convention with clear verb prefixes: probe, probe_batch, list_formats, list_targets. The naming style is uniform and predictable, making the tool set easy to reason about.

Tool Count5/5

With exactly 4 tools, the server is tightly scoped for its purpose of document inspection. Each tool fills a necessary role (single file, batch, format discovery, target discovery) without redundancy or bloat, fitting well within the ideal 3–15 range.

Completeness5/5

The surface covers all core workflows: probing an individual file, probing many files efficiently, discovering supported formats, and enumerating probe targets for a given format. There are no obvious dead ends or missing operations for the server's stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

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