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Found 1,408 Skills
When the user wants to design, optimize, or improve lead qualification forms and processes. Also use when the user mentions "lead scoring," "qualification criteria," "BANT," "discovery questions," "intake form," "lead routing," "MQL," "SQL," or "qualification framework." This skill covers capturing the right information to qualify and prioritize sales leads effectively.
Methodology for detecting client SOC patches, attacker activity, and security-state changes that occur DURING a red-team engagement — and converting those observations into deliverable findings. Built from authorized red-team work where the client patched a confirmed SQLi within 30 minutes of detection AND an external attacker locked multiple new accounts during a single test session. Use when (a) running ANY active engagement against a monitored target, (b) a previously-confirmed finding stops reproducing, (c) baseline timing shifts unexpectedly, or (d) you notice response patterns changing during testing.
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and reference templates/snippets (vector/hybrid/image) plus agent-oriented examples (RAG/memory/text2sql).
Use when managing Oracle Autonomous Database on OCI, troubleshooting performance issues, optimizing costs, or implementing HA/DR. Covers ADB-specific gotchas, cost traps, SQL_ID debugging workflows, auto-scaling behavior, and version differences (19c/21c/23ai/26ai).
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.
Build end-to-end real-time data pipelines with Kafka, PostgreSQL, Airflow, and Streamlit using Medallion Architecture for streaming analytics.
Read-only audit of a database layer — schema anti-patterns (EAV, generic keys, imprecise types), query and index fit (SELECT *, N+1, unindexable predicates), integrity and concurrency, migration and tenancy hygiene — with evidence per finding and a SHIP / FIX / BLOCK verdict. Use when asked to audit the database, review the schema or migrations, judge a data model, or 'проверь схему базы'. Never edits schema or data. Do not use for runtime profiling (awesome-performance-audit), SQL injection (awesome-security-audit), or data-access style (awesome-code-standards).
Create reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains for any language, installing system-level dependencies (compilers, databases, native libs like openssl/BLAS), pinning exact package versions for a team, running local services (PostgreSQL, Redis, Kafka), onboarding developers with one command, or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.
Report the health, performance, resource status, and actual costs of applications deployed by qianwenai-deploy to the Alibaba Cloud China site (aliyun.com) in natural language, without entering the console. Read the .qianwenai-deploy state file in the project directory to identify the application and its ECS (and optional RDS MySQL) resources, then call read-only cloud APIs to summarize application availability, ECS/RDS performance, and costs in RMB. Use cases: users ask how a deployed application is running, want a health/performance/cost overview, are concerned about CPU/memory/connection count/slow SQL risks, or ask about the monthly cost of an application deployed by qianwenai. Non-use cases: there is no .qianwenai-deploy state file; the target is the Alibaba Cloud international site (use qwencloud-observe); or the user wants to change or restore resources (use qianwenai-operate).
Turn wiki golden pages into a CI-blocking eval suite with a cheap→expensive assertion cascade plus a committed regression baseline. Goldens are md files under llmwiki/wiki/sources/evals/ with YAML frontmatter (input, expected, optional rubric, asserts). The engine runs deterministic tier-1 asserts (equals/contains/regex/is-json/is-sql-ish) in pure code, an optional tier-2 similarity, and reports tier-3 (LLM-rubric judge) as the quarantined adapter — never calling a model. Candidate outputs come from --outputs outputs.json so the suite is fully runnable without any model. Trigger when the user says "wikieval", "eval suite for the wiki", "regression gate for goldens", "assertion cascade", "block CI on eval drop", or invokes /wikieval.