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GitHub 저장소

openfuse

openfuse에는 tma1-ai에서 수집한 skills 11개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.

수집된 skills
11
Stars
32
업데이트
2026-06-17
Forks
2
직업 범위
직업 카테고리 3개 · 100% 분류됨
저장소 탐색

이 저장소의 skills

backend-dev-guidelines
소프트웨어 개발자

Shared backend guide for Langfuse's Next.js, tRPC, BullMQ, and TypeScript monorepo. Use when creating or reviewing tRPC routers, public REST endpoints, BullMQ queue processors, backend services, middleware, Prisma or ClickHouse data access, OpenTelemetry instrumentation, Zod validation, env configuration, or backend tests across web, worker, or packages/shared.

2026-06-17
seed-test-data
소프트웨어 품질 보증 분석가·테스터

Seed local Langfuse test data with one command: large/branching observation trees (v3 and v4 events), long sessions, bulk traces for list performance. Use whenever a task needs ClickHouse/Postgres test data — e.g. "seed a complex trace", "make a tough session", "fill the trace list", "test v4 events UI", or when debugging trace/session/list rendering or performance. Never write ad-hoc seed scripts or raw ClickHouse inserts.

2026-06-11
weekly-production-review
네트워크·컴퓨터 시스템 관리자

Prepare Langfuse weekly production reviews that explain what broke, what was fixed, what remains open, and where alerting or tracking needs cleanup. Use when asked for a production review, "what broke last week", fixed/open bugs, Datadog alerted monitors/pages, status-page incidents, incident.io incidents, or an engineering-team overview that combines Linear, Datadog, and customer incident signals.

2026-06-08
code-review
소프트웨어 품질 보증 분석가·테스터

Shared code review workflow for Langfuse. Use when reviewing a PR, branch, diff, or local changes for correctness, regressions, risk, and missing tests. Start with references/review-checklist.md for repo-specific review rules and use package AGENTS.md files plus any matching shared skills when the change touches those areas.

2026-06-08
frontend-large-feature-architecture
소프트웨어 개발자

Use when building, changing, or refactoring large Langfuse frontend features, virtualized lists, large tables, controller components, local feature state, Zustand stores, row selection, high-frequency UI state, or rendering-performance issues.

2026-06-05
storybook
소프트웨어 개발자

Use when writing or reviewing Storybook stories (`.stories.tsx`) for React components.

2026-06-04
add-model-price
소프트웨어 개발자

Use when editing worker/src/constants/default-model-prices.json, packages/shared/src/server/llm/types.ts, pricing tiers, tokenizer IDs, or matchPattern regexes for OpenAI, Anthropic, Bedrock, Vertex, Azure, or Gemini model pricing.

2026-06-03
clickhouse-best-practices
소프트웨어 개발자

MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 28 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.

2026-06-03
pnpm-upgrade-package
소프트웨어 개발자

Upgrade pnpm workspace dependencies to target/latest versions: direct/transitive bumps, release-age checks, temporary overrides, minimumReleaseAgeExclude, lockfile/dedupe verification.

2026-06-03
datadog-query-recipes
네트워크·컴퓨터 시스템 관리자

Langfuse-specific Datadog query recipes for production telemetry research. Use when asked to investigate tenant or project activity, public API endpoint usage, queue consumer behavior, spans, logs, metrics, or ad hoc production questions across prod-us, prod-eu, prod-hipaa, and prod-jp. This skill is for reusable query shapes and measured research; pair it with debug-issue-with-datadog when the task is an incident or root-cause analysis.

2026-05-27
debug-issue-with-datadog
소프트웨어 개발자

Debug a user-reported issue, Linear ticket, or incident report by combining Datadog (APM, logs, metrics) with the Langfuse repo to establish a root cause. Use when given a Linear issue URL/ID (e.g. LFE-XXXX), a GitHub issue, or a pasted error/report and asked to investigate, root-cause, or triage. Produces a structured analysis — error breakdown, hypothesis-by-class, suggested patches with code references.

2026-05-11