Bootstrap Repo Analysis
langchain-ai/open-swe/agent/skills/bootstrap-repo-analysiscodingResmi
Resmi Sağlayıcı Skill'iView repo
First-time analysis of a repository with no prior reviewer outcomes. Crawl historical merged-PR review feedback with the gh CLI (plus any preloaded samples), extract the team's review norms, and synthesize the initial per-repo review-style prompt. Use this for a cold-start repo; use continual-learning instead once the reviewer has accumulated finding outcomes.
Dosyalar1 dosya
SKILL.md62 satır
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Kurulum
ÖnerilenTek komut — ajanınız otomatik olarak devreye alır.
Kurulum komutunu görmek için yukarıdan bir AI aracı seçin.
veya
Manuel Kurulum
Daha fazla adımDosyayı indirin ve ajanınızın sistem istemine yapıştırın.
Skill detayları
Versiyonv1.0.0
YazarLangChain AI
Kategoricoding
Skill IDlangchain-ai/open-swe/agent/skills/bootstrap-repo-analysis
İlgili skill'ler
Continual LearningNightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt, and save the refined version. Use this once outcomes exist; use bootstrap-repo-analysis for a cold-start repo.Code ReviewPerform a structured code review of changes, checking for correctness, style, tests, and potential issues.Coding PrefsRead the user's coding preferences from /memory/coding-prefs.md before making non-trivial style decisions, and append new preferences when the user gives durable feedback.Langgraph DocsFetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.Langgraph DocsFetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.PlanningBreak down a coding task into a structured implementation plan with clear steps, file identification, and risk assessment.