convex-insights

Разобрать ошибки и состояние приложения Convex

get-convex/agent-skillsОт разработчика платформы
64звёзд11форковУ всего репозитория

Что получите

Краткий вывод с количеством событий, характерным примером ошибки или записи журнала и, когда возможно, ссылкой на соответствующий экран Convex Dashboard.

Что передать

Развёртывание Convex и вопрос; при необходимости — функция или идентификатор запроса.

Автопроверка файлов

Проверен состав файлов. Запуск не тестировался. Что проверено

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Как использовать

Помогает разработчикам работающего приложения Convex выяснить, какие вызовы завершаются ошибкой, почему не удался конкретный запрос и какие сигналы проблем есть у развёртывания. Выводы сопровождаются данными для проверки.

  1. Укажите, какое развёртывание нужно изучить и что вас интересует: ошибки, состояние или отдельный вызов.
  2. Для конкретного сбоя передайте известные функцию и идентификатор запроса.
  3. Если проверяете последствия обновления, попросите сопоставить начало ошибок с версией развёртывания.

Условия работы

  • Используется официальный MCP Convex; работа ограничена чтением, без изменений и включения разрешений на изменение рабочей среды.
  • Просмотр состояния доступен только для облачных сред разработки и рабочей среды с пользовательской авторизацией.
  • Журналы выбираются по числу последних записей и фильтруются локально; совпадение с обновлением не доказывает причинную связь.
  • Исправление кода, производительности и стоимости передаётся другим скиллам.

Пример запроса после установки

Разбери ошибки в указанном развёртывании Convex после последнего обновления. Сгруппируй их по функциям, покажи подтверждающие записи и ссылку для проверки.

Пример составлен по инструкции автора; результат запуска не проверялся.

Основание: инструкция закреплённой версии

Для установки

Node.js, npm и Git для команды выше. Подключения и инструменты для работы скилла настраиваются отдельно.

Совместимые агенты

Совместимость указана для инструкций. Запуск в каждом приложении не тестировался; для веб-чата способ подключения может отличаться.

Файлы скилла

GitHub
Читать инструкцию SKILL.md

Исходный текст закреплённой версии.

---
name: convex-insights
description: "Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link."
---

<!-- GENERATED from convex-agents content/capabilities/convex-insights.json — do not edit by hand. -->

# Query logs + health in natural language

The deployment already records what happened; the agent just has to ask well. This capability is a disciplined wrapper over the official Convex MCP's read tools (`logs`, `insights`, `functionSpec`, `status`) that turns operational questions into narrow, evidence-returning queries and hands back answers a human can one-click verify in the dashboard. The discipline is copied from the observability MCP surface that works best in the wild: discover fields before querying, three views not fifteen tools, token-frugal output, and a dashboard deep link on every answer.

## Workflow

1. GUARD: deploy-guard step 0-1 — identify + announce which deployment is being read. Reading logs/insights is read-only; never enable prod mutation flags for an insights pass.
2. DISCOVER before you query — never guess identifiers. Use `functionSpec` to list the real function names and `status` for the deployment/version. Note the tool limits up front: `logs` takes only `--history <n>` (a COUNT, not a time window), `--success`, `--jsonl`, `--prod`, `--deployment` — there is NO server-side status/function/requestId/time filter; `insights` has no function filter and is cloud dev/prod + user-auth only. So you fetch a recent window and filter CLIENT-SIDE.
3. PICK ONE OF THREE VIEWS and fetch the raw window, then filter locally:
   - failures view → `logs --history <n> --jsonl`, then locally keep failures + group by function + error message, returning counts + the first stack per group. Answers 'what's erroring', 'what failed after deploy'.
   - health view → `insights` (cloud only): the typed 72h read-limit / OCC events. Surface + rank them, but hand perf/cost ROOT-CAUSING and fixes to convex-advisor — emit those as pointer findings, do not own the perf-fix framing here.
   - trace view → `logs --history <n> --jsonl` then locally filter to one requestId/function to read the full execution. Answers 'why did THIS call fail'.
4. SCOPE by fetching a bounded recent window (a sensible `--history` count) and filtering client-side to the function/status/requestId asked about; when the window is large, aggregate (counts by function/message) rather than dumping lines.
5. ANSWER with (a) the one-line finding, (b) the evidence (counts + one representative stack/log line), and (c) WHEN POSSIBLE an agent-constructed dashboard deep link (dashboard.convex.dev, the deployment's Logs/Functions view) for human verification — no tool returns the link, so build it from the deployment name + function; never a raw log dump as the answer.
6. CROSS-CHECK deploy causality when asked 'did my deploy break this': compare the failure onset (from the log timestamps) against the deployment version from `status`; correlate, don't assert.
7. HAND OFF, don't fix here: a perf/cost cause → convex-advisor (which owns those fixes); a code defect → convex-reviewer/convex-authz; a live error to react to going forward → monitor/sentinel. Emit findings on the bus (specs/finding.schema.json) — primarily `observability`, with perf/cost as pointer findings to advisor — so a composite pass can pick them up.

## Rules

- Discover real function/field names (functionSpec/status) before filtering — never guess identifiers, never return a confusing empty result for a name the app doesn't have.
- `logs` and `insights` have NO server-side status/function/requestId/time-window filter (logs takes only a --history COUNT; insights is cloud-only) — fetch a bounded recent window and filter CLIENT-SIDE; say so rather than implying params that don't exist.
- One of three views per question (failures / health / trace) — don't fan out into many speculative tool calls.
- No tool returns a dashboard link — construct it from the deployment name + function when possible for human verification; never answer with a raw log dump.
- Read-only always: an insights pass runs no mutation and never enables prod mutation flags (deploy-guard discipline).
- Stay a reader and defer perf/cost fixes to convex-advisor: emit primarily `observability`, route perf/cost as POINTER findings so advisor uniquely owns the perf-fix framing; forward-looking reaction goes to monitor/sentinel.

Проверка и особенности

Автоматическая проверка источника и файлов

Автоматически проверены публичный репозиторий, лицензия, заголовок SKILL.md, состав текстового пакета и Git-хеш каждого файла. Пакеты с исполняемыми файлами и срабатываниями применённых статических правил не включены. Ручной аудит всех инструкций и функциональный запуск не проводились. Внешние инструменты и сервисы не проверялись. Проверка не гарантирует безопасность.

В публичном списке установок на 2026-10-09 у скилла было 30 273 установок. Порог отбора — 1 000 установок. Число установок показывает распространённость, а не качество или безопасность инструкции.

Проверка состава
09.10.2026
Проверенная версия
2cfe645c87f9
Файлы с кодом
Не указаны в данных проверки
Изменения на GitHub
Нужна повторная проверкаПоследняя проверка: 11.10.2026
Как мы проверяем скиллы

Репозиторий и лицензия

get-convex/agent-skills
64 звёзд11 форков

Это показатели всего репозитория, а не установки скилла. Снимок требует обновления.

Последняя активность GitHub
02.10.2026
Лицензия
Apache-2.0
Добавлен в каталог
09.10.2026
Полный текст лицензии
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