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Found 101 Skills
Comprehensive testing doctrine for software and AI systems — covers positive patterns, anti-patterns, gates for coding agents writing tests, CI discipline, and an LLM/agent evaluation primer. Use when authoring or reviewing tests, adding mocks, deciding test placement, generating tests via agents, debugging flaky CI, designing eval suites for LLM features, or rebuilding a brittle test suite. Contains 12 positive patterns (selector hierarchy, table-driven, builders, real-system gates), 25 anti-patterns across Brittleness, Flakiness, Mock-misuse, Process, and AI-specific families, 7 mandatory gates for agents writing tests, flaky-test taxonomy with quarantine workflow, contract / property / mutation testing patterns, and an oracle-ladder primer for LLM-as-judge and agent eval. Language-agnostic — pseudo-code only. Don't use for general code review, library-specific debugging unrelated to tests, non-testing CI pipeline design, or production observability.
Read an academic paper end to end and extract professional research insights, figures, metadata, and critique. Use this skill whenever the user shares a scientific paper, review paper, survey paper, systematic review, meta-analysis, scoping review, arXiv link, DOI, PDF, or pasted paper text and asks to read, summarize, analyze, extract, digest, review, critique, or explain it. For original research papers, produce a modified Heilmeier analysis. For review literature, produce a field-map extraction covering scope, taxonomy, evidence quality, consensus, controversies, gaps, and future directions. Do NOT use this skill for non-academic articles, blog posts, or news.
Structured session analysis and project instruction refinement using a five-type intervention taxonomy (Correction, Repetition, Role Redirect, Frustration Escalation, Workaround) with severity scoring to categorize process gaps. Refines project instructions (CLAUDE.md, AGENTS.md, .team/coordinator-instructions.md) with structural (not advisory) language, maintains WORKING_STATE.md for crash recovery (read-first-after-any- interruption protocol), and implements a self-reminder protocol (re-read constraints every 5-10 messages to prevent role drift). Includes advisory- to-structural promotion pattern for recurring gaps. Activate after milestones, repeated user corrections, session restarts, crash recovery, every 5 completed tasks, or on user request. Triggers on: "reflect on this session", "why do I keep correcting you", "update project instructions", "update working state", "session retrospective", "crash recovery", "context compaction", "role drift", "I keep telling you the same thing", "analyze my corrections". Also relevant when the agent notices repeated corrections, needs to resume after compaction, or wants to prevent known failure modes from recurring.
Use this skill when optimizing e-commerce sites for search engines - product page SEO, faceted navigation crawl control, category taxonomy, product schema markup, pagination handling, inventory-aware SEO (out-of-stock pages), and e-commerce site architecture. Triggers on any task involving online store search optimization, product listing pages, shopping search results, or e-commerce technical SEO challenges.
Neta API community skill — browse interactive feeds, view collection details, like and interact with content, and browse content by tags and characters in a community context. Use this skill when the user wants to “see what people are making”, “scroll the feed”, or “interact with works”. Do not use it for taxonomy/keyword‑level research (handled by neta-suggest) or for generating images/videos/songs (handled by neta-creative).
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
Guide identification, measurement, and management of operational risk in trading and brokerage operations. Use when designing trade error detection and correction procedures, investigating trade breaks and reconciliation failures, classifying loss events under Basel taxonomy, developing key risk indicators (KRIs) and dashboards, responding to system outages or data feed failures or order routing errors, conducting root cause analysis after a trade error or settlement fail, planning business continuity and disaster recovery for trading desks, preparing for FINRA or SEC operational risk examinations, or assessing technology risk in OMS and market data systems. Also covers fat-finger errors, error account P&L, and corrective action tracking.
Audit a skill repository or installed skill collection for global consistency, lifecycle coverage, routing quality, documentation drift, memory writeback coverage, stale future-skill references, broken helper paths, and validation readiness. Use this skill whenever the user asks for a global consistency audit, skill taxonomy review, lifecycle audit, cross-skill routing audit, README or AGENTS inventory consistency check, or maintenance pass over a collection of agent skills.
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).
Use when a security incident has been detected or declared and needs classification, triage, escalation path determination, and forensic evidence collection. Covers SEV1-SEV4 classification, false positive filtering, incident taxonomy, and NIST SP 800-61 lifecycle.
Deep formal test smell audit based on academic research taxonomy (testsmells.org). Detects 19 categorized smell types — conditional logic, mystery guests, sensitive equality, eager tests, and more — with calibrated severity and research-backed remediation. Use for comprehensive test suite health assessments. For a quick pragmatic review, use test-anti-patterns instead. DO NOT USE FOR: writing new tests (use writing-mstest-tests), evaluating assertion quality specifically (use assertion-quality), or finding test duplication and boilerplate (use exp-test-maintainability).
Use when working with WordPress core APIs in plugins or themes. Covers add_menu_page, add_submenu_page, add_options_page, add_shortcode, add_meta_box, register_post_type, register_taxonomy, HTTP API (wp_remote_request, wp_remote_get, wp_remote_post), wp_schedule_event (WP-Cron), wp_add_dashboard_widget, users and roles (add_role, current_user_can), privacy tools (wp_register_personal_data_exporter), theme mods, site health API, global variables ($wpdb, $post, $wp_query), add_image_size, responsive images, and advanced hooks (do_action, apply_filters, remove_action).