langfuse/langfuse

create-repo-agent

Design, implement, review, or harden Langfuse repo-owned autonomous agents.

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Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Create Repo Agent

Purpose

Build repo agents that can run unattended without granting the model broad write credentials, arbitrary shell, or uncontrolled network access. The default architecture is a read-only audit job that produces a validated patch artifact plus a separate publisher job that owns GitHub writes.

Use this skill together with the domain skill for the files the agent will maintain. For example, a pricing agent must also use add-model-price.

Required Reading

For every repo agent task, read these references before designing or editing:

  1. references/security-standards.md
  2. references/workflow-blueprint.md when implementing or changing a GitHub Actions workflow
  3. references/review-checklist.md before final review or PR publication

Workflow

  1. Define the exact maintenance objective, allowed files, external sources, expected no-change behavior, and PR ownership.
  2. Choose the least-capable runtime: prefer a scheduled/manual GitHub Action with read-only repository checkout and no write credentials in the LLM step.
  3. Encode the prompt with explicit allowed edit surfaces, hard constraints, source-evidence requirements, and structured output.
  4. Give the agent only scoped file tools, domain-scoped fetch tools, and exact deterministic validator commands.
  5. Validate the diff independently of the agent, including untracked files, path allowlists, git diff --check, line-count limits, and domain-specific validators.
  6. Publish from a separate job or step after validation, using a bot credential only for branch push and PR create/update.
  7. If self-improvement is allowed, constrain it to named workflow or skill-reference files and require security invariants to remain unchanged.
  8. Run agent setup checks when .agents/** changes, then publish a normal human-reviewable PR.

Non-Negotiables

  • Never expose a write-capable GitHub token, PAT, GitHub App token, OIDC token, SSH key, cloud credential, or package-publishing token to the LLM agent step.
  • Never rely on prompt instructions as the only security boundary. Enforce file and command limits outside the agent.
  • Never stage a directory wholesale. Stage only the validated file list.
  • Never ignore untracked files in diff validation.
  • Never let self-improvement bypass the same diff allowlist and human PR review as normal edits.
  • Never grant arbitrary Bash, curl, wget, gh, git push, package-manager, interpreter, environment-dump, or process-inspection tools to the LLM agent.
  • Never add id-token: write unless the agent truly needs OIDC and the trust relationship is reviewed explicitly.
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Weitere Skills

Alle Skills
langfuse
Offiziell

add-model-price

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.

Installationen
1
GitHub Stars
34.447
Aktualisiert
10. Sept.
langfuse
Offiziell

agent-setup-maintenance

Shared workflow for editing Langfuse's repo-owned agent setup under .agents/. Use when changing AGENTS files, shared skills, .agents/config.json, generated shim behavior, provider discovery paths, or install-time agent sync.

Installationen
1
GitHub Stars
34.447
Aktualisiert
10. Sept.
langfuse
Offiziell

analyze-cloud-costs

Analyze Langfuse Cloud infrastructure cost structure using Metabase cost marts. Use when asked about cloud spend, AWS versus ClickHouse cost splits, cost drivers by provider/service/usage type/account, daily cost per tracing event, infra cost dashboards, or cost regressions visible in Metabase.

Installationen
1
GitHub Stars
34.447
Aktualisiert
10. Sept.
langfuse
Offiziell

backend-dev-guidelines

Build or review Langfuse backend code. Use for tRPC routers, public REST APIs, BullMQ processors, services, middleware, Prisma or ClickHouse access, OpenTelemetry, Zod, environment configuration, or backend tests.

Installationen
1
GitHub Stars
34.447
Aktualisiert
10. Sept.