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Found 170 Skills
Deep analysis and investigation
Expert in SRE practices, incident management, root cause analysis, and automated remediation.
AI agent applies a 5-phase systematic framework for tackling complex problems when conventional approaches fail. Use when stuck, blocked, or troubleshooting issues.
Convenes expert panels for problem-solving. Use when user mentions panel, experts, multiple perspectives, MECE, DMAIC, RAPID, Six Sigma, root cause analysis, strategic decisions, or process improvement.
Evidence-based investigative code review using deductive reasoning to determine what actually happened versus what was claimed. Use when verifying implementation claims, investigating bugs, validating fixes, or conducting root cause analysis. Elementary approach to finding truth through systematic observation.
Security Incident Report templates drawing from NIST/SANS. DDoS post-mortem, CVE correlation, timeline documentation, and blameless root cause analysis. Use when working with incident report, post-mortem, sir, ddos analysis, security reporting, root cause analysis, cve correlation, nist 800-61.
Evidence-based test debugging enforcing systematic root cause analysis. Use when tests are failing, pytest errors occur, test suite not passing, debugging test failures, or fixing broken tests. Prevents assumption-based fixes by enforcing proper diagnostic sequence. Works with Python (.py), JavaScript/TypeScript (.js/.ts), Go, Rust test files. Supports pytest, jest, vitest, mocha, go test, cargo test, and other frameworks.
Scientific method expert for systematic bug investigation and root cause analysis. Use when users report bugs, crashes, unexpected behavior, or debugging requests. Applies hypothesis-driven investigation, controlled experiments, and rigorous validation across any programming language or platform.
Evidence-based 4-phase root cause analysis: Reproduce, Isolate, Identify, Verify. Use when user reports a bug, tests are failing, code introduced regressions, or production issues need investigation. Use for "debug", "fix bug", "why is this failing", "root cause", or "tests broken". Do NOT use for feature requests, refactoring, or performance optimization without a specific bug symptom.
Follow this sub-process when fixing bugs—turn the verbal description of "discovered a problem" into a closed loop of verification and repair, leaving three documents in the middle: issue report, root cause analysis, and repair record. This process adds a buffer between "seeing the problem" and "starting to modify code", avoiding several common pitfalls: the problem description in your mind disappears after modification, fixing only the surface without analyzing the root cause, uncontrollable expansion of repair scope that cannot be traced, and not knowing if the fix is correct without verification after modification. This skill only acts as a router, deciding which of report / analyze / fix to proceed with based on existing outputs. For simple problems that can be identified at a glance, a fast track will be taken, skipping the two middle steps and only keeping the fix-note.
Guides technical support engineering—customer ticket investigation, reproduction, log and API analysis, root-cause isolation, workaround communication, engineering escalation with evidence, and knowledge-base fixes for product bugs and integration issues. Use when debugging a customer-reported issue, writing a repro for engineering, analyzing API errors, drafting technical replies, or improving support runbooks—not for CS program design, renewals, or billing ops (customer-ops-specialist), production incident command (incident-management-engineer), building product features (fullstack-software-engineer), or company-wide crisis statements and launch announcements (communication-lead), or exec/VIP and community escalation program design (community-executive-escalations-program-manager). Product how-to, macros, and ticket triage without deep debugging: product-support-specialist.
Debugging méthodique en 4 phases (reproduce → isolate → fix → verify). Use when investigating a bug, regression, flaky test, or unexpected behavior.