「root cause」の検索結果

Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.

日本語の概要は準備中です。原文の説明を表示しています。

Repair one concrete reproducible build, typecheck, lint, test, packaging, or CI failure with a bounded root-cause-first loop; do not trigger for runtime bugs without a failing gate, broad test strategy, dependency/toolchain migration, or generic implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnoses LLM output failures including hallucinations, constraint violations, format errors, and reasoning issues. Provides root cause classification, prompt fixes, tool improvements, and new test cases. Use for "debugging AI", "fixing prompts", "quality issues", or "output errors".

日本語の概要は準備中です。原文の説明を表示しています。

Creates comprehensive post-incident documents with timeline, root cause analysis, contributing factors, action items, and ownership. Follows SRE best practices for blameless postmortems. Use for "postmortem", "incident review", "RCA", or "post-incident".

日本語の概要は準備中です。原文の説明を表示しています。

Diagnoses and fixes flaky tests by identifying root causes (timing issues, shared state, randomness, network dependencies) and provides stabilization strategies. Use for "flaky tests", "test stability", "intermittent failures", or "test debugging".

日本語の概要は準備中です。原文の説明を表示しています。

Use when a Claude Code session loops, drifts from scope, claims a fix that CI rejects, hits context, PATH, or permission walls, or fails in a way another retry will not solve and a root cause diagnosis is needed instead.

日本語の概要は準備中です。原文の説明を表示しています。

Complete reference for 26 web2 bug classes with root causes, detection patterns, bypass tables, exploit techniques, and real paid examples. Covers IDOR, auth bypass, XSS, SSRF (11 IP bypass techniques), SQLi, business logic, race conditions, OAuth/OIDC, file upload (10 bypass techniques), GraphQL, LLM/AI (ASI01-ASI10 agentic framework), API misconfig (mass assignment, JWT attacks, prototype pollution, CORS), ATO taxonomy (9 paths), SSTI (Jinja2/Twig/Freemarker/ERB/Spring), subdomain takeover, cloud/infra misconfigs, HTTP smuggling (CL.TE/TE.CL/H2.CL), cache poisoning, MFA bypass (7 patterns), SAML attacks (XSW/comment injection/signature stripping), error disclosure / debug endpoints (stack trace regex per framework, chain templates), CSS injection (attribute-selector exfiltration, opacity clickjacking, @import). LFI / file inclusion -> RCE (php://filter source disclosure, iconv filter-chain RCE with no upload, log/environ poisoning, .user.ini/.htaccess auto_prepend, data:// + expect:// wrappers, session inclusion, traversal bypass table). Insecure deserialization (PHP __wakeup bypass / phar:// POP chains, Java ysoserial CommonsCollections gadgets + magic bytes, Python pickle __reduce__ + signed-cookie forgery, Node node-serialize). Dependency confusion / supply chain (internal package-name discovery, unclaimed-name confirmation, callback-only PoC, npm/pip/Maven/RubyGems variants). Use when hunting a specific vuln class or studying what makes bugs pay.

日本語の概要は準備中です。原文の説明を表示しています。

Deep bug analysis to break the fix-forget-repeat cycle. Analyzes root cause category, why fixes failed, prevention mechanisms, and captures knowledge into specs. Use after fixing a bug to prevent the same class of bugs.

日本語の概要は準備中です。原文の説明を表示しています。

Investigates DAG incidents with a precise top event, timeline, competing hypotheses, barriers, propagation, and bounded recovery. NOT for automated root-cause classification, trace collection, or performance profiling.

日本語の概要は準備中です。原文の説明を表示しています。

Designs or reviews provenance-bound DAG attempt traces, coverage gaps, cancellation, and unknown-effect reconciliation. NOT for claiming execution completeness, deployment monitoring, or root-cause proof.

日本語の概要は準備中です。原文の説明を表示しています。

Naturalistic causal reasoning for failures and disputed attribution. Use when postmortems or root-cause debates need reframing. NOT for causal inference, fault trees, or fully observed failures.

日本語の概要は準備中です。原文の説明を表示しています。

Naturalistic causal reasoning for failures and disputed attribution. Use when postmortems or root-cause debates need reframing. NOT for causal inference, fault trees, or fully observed failures.

日本語の概要は準備中です。原文の説明を表示しています。