Loading...
Loading...
Found 765 Skills
Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Follow this sub-process when fixing bugs — turn the verbal description of "problem found" into a closed loop from verification to repair, leaving three documents: problem report, root cause analysis, and repair record. This process adds a buffer between "seeing the problem" and "starting to modify code" to avoid common pitfalls: the problem description in your mind disappears after the fix, you only fix the surface without analyzing the root cause, the scope of repair expands and cannot be traced, and you don't know 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 artifacts. For simple problems that can be identified at a glance, a fast track will be taken, skipping the two middle steps and only retaining the fix-note.
Comprehensive reference for LINE Messaging API — webhook setup, message sending, Flex Message design, Rich Menu management, audience targeting, insights, coupons, and channel access tokens. This skill should be used when the user asks to "build a LINE Bot", "set up a webhook", "send a push message", "design a Flex Message", "create a Rich Menu", "manage audience targeting", "get messaging insights", "create a coupon campaign", "debug webhook signature verification", or mentions LINE Messaging API, LINE OA chatbot, reply/push/multicast/narrowcast/broadcast, Flex Message JSON, Rich Menu, group chat bot, channel access token, or URL schemes. Always use this skill whenever the user mentions LINE bots, chatbots, LINE OA, or any messaging-related LINE integration, even if they don't explicitly say "Messaging API".
Background knowledge for droid-control workflows -- not invoked directly. Deliverable verification against commitments.
Local pentest sandbox for a full black-box engagement. Triggers on "kage", "pentest", "security audit on", "audit the security of". Runs recon, deep testing, exploit verification, and judging inside a per-engagement Kali Docker container. Each host working directory gets its own isolated sandbox. Produces `./results/<target>/audit-report.md`.
Fireflies.ai platform help — AI meeting note-taker with GraphQL API, webhooks (V1 + V2), AskFred AI, real-time events, and Fred bot that joins Zoom/Meet/Teams to transcribe. Use when Fireflies transcripts not syncing to CRM, webhooks not firing or signatures failing HMAC verification, hitting 50 req/day or 60 req/min rate limits on the GraphQL API, building a transcript pipeline from Fireflies to Snowflake/BigQuery/warehouse, migrating from Webhooks V1 to V2, the Fireflies bot not joining calls or users wanting to disable auto-join, deciding between Free, Pro ($10), Business ($19), or Enterprise ($39) tier, or wiring AskFred or Real-time API into an internal app. Do NOT use for comparing Fireflies vs Fathom/Avoma/Gong or selecting a note-taker (use /sales-note-taker) or reviewing a single sales call for coaching (use /sales-call-review).
Arrfounder platform help — founder revenue directory by @Folyd (2024) that auto-extracts MRR/ARR + products from Twitter/X bios via AI, lists 1000+ founders on sortable leaderboards (ARR / followers / products / recently added), free Airtable submission with 24-48h manual approval, auto-syncs within hours of bio changes. Social-proof verification only (no Stripe / Lemon Squeezy / Polar API integration) — built for peer discovery and community browsing, not acquisition-grade proof. Use when getting listed on Arrfounder, writing a Twitter/X bio that passes the MRR/ARR extractor, fixing a profile that didn't get approved or stopped updating after a bio edit, deciding Arrfounder vs TrustMRR or StartuPage for verified-revenue display, benchmarking against peers in the $1K-$10M+ ARR tiers, or using Arrfounder as a comp-check tool before pricing a sale or fundraise. Do NOT use for selling/buying a project or cross-marketplace valuation (use /sales-side-project-valuation).
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification
Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop
Implement a task with automated LLM-as-Judge verification for critical steps
Use when starting task work that needs branch isolation, before planning or coding — creates a worktree branching from current remote main with freshness verification and project setup