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Found 205 Skills
Read your daily Working Memory briefing to understand current context. Contains active focus areas, priorities, unresolved flags, and recent knowledge changes. Load this automatically at the beginning of sessions for cross-tool continuity.
Capture solved problems as categorized documentation with YAML frontmatter for fast lookup
Search your personal knowledge base when past insights would improve response. Recognize when stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests.
One-stop companion and installer for the official Tencent IMA skill (腾讯 IMA / ima.qq.com). Handles zero-config installation to Claude Code / Codex / OpenClaw via `npx skills add`, guides API key setup, detects and fixes known issues in the upstream package (including the missing-YAML-frontmatter bug in submodule SKILL.md files), and implements a personalized fan-out search strategy with priority-based knowledge base boosting. Use this skill whenever the user mentions IMA, 腾讯 IMA, ima.qq.com, ima-skill, installing or configuring ima-skill, searching across IMA knowledge bases, 知识库搜索, 笔记搜索, fan-out search with preferred KBs, or reports errors like "Skipped loading skill(s) due to invalid SKILL.md". Also trigger for any request to diagnose, repair, or personalize the behavior of an ima-skill installation. This is a wrapper layer around ima-skill — it installs and orchestrates ima-skill rather than replacing it.
A Web/JS reverse engineering case knowledge base extracted from 42 articles across the entire 1997.pro site. It applies to case clues such as Akamai/Kasada/PX/reese84/TongDun/a_bogus/Tencent slider/Alibaba slider/JSVMP/227/226/wasm/protobuf/rid/fuid/fs/bx-pp/run_js/storage.estimate/animationend, as well as scenario judgment, method routing and case comparison for risk control fingerprints, environment patching, JSVMP/flat flow/WASM, captchas, and protocol parameter chains; it is used in collaboration with web-js-reverse-master-flow and three MCPs: jshook + js-reverse + chrome-devtools-mcp by default.
Research customer questions by searching across documentation, knowledge bases, and connected sources, then synthesize a confidence-scored answer. Use when a customer asks a question you need to investigate, when building background on a customer situation, or when you need account context.
Generate hierarchical AGENTS.md knowledge base for a codebase. Creates root + complexity-scored subdirectory documentation.
Process raw source documents into wiki pages. Use when the user adds files to raw/ and wants them ingested, says "process this source", "ingest this article", "I added something to raw/", or wants to incorporate new material into their knowledge base.
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
This skill should be used when the user asks to start a new research project, import an existing code-plus-Markdown repository into Obsidian, or bind the current repository to a compact research knowledge base for future syncing.
End-of-session knowledge cleanup with OCD-level rigor — reconciles project docs (CLAUDE.md, README.md, docs/) and agent memory against the code so nothing rots. OCD-level review and synchronization of project documents and agent memory after a session. MUST trigger when the user says: "sync up", "tidy up docs", "update memory", "clean up docs", "/sync", "/neat", "sync up", "tidy up docs", "tidy up", "update memory", "organize", "wrap up", "this phase is done", "newcomers can start directly", or any phrase suggesting a development milestone where knowledge needs reconciliation. Also trigger when the user reports stale docs, conflicting memories, or wants a clean handoff to teammates or other agents. A standalone "tidy" with prior development context counts — do not under-trigger. Cross-platform: works on Claude Code, OpenAI Codex, OpenCode, and OpenClaw.
Technical Document Knowledge Base (LLM Wiki) for Alibaba Cloud Tongyi Qianfan Platform. Activated when users inquire about Qianfan-related issues such as model lists, API parameters, error codes, application development (Agent/RAG/Knowledge Base/Memory/Plugins), model comparison and pricing, SDK/OpenAI compatible interfaces, multimodal capabilities (speech/image/video), Token billing, etc. It includes structured model market data in models (including contextWindow/QPM/pricing/sample code), wiki synthesis layer (topic pages/concept pages/comparison pages), and raw original document layer; for model specification issues, check models/index.md first, and for document-related issues, check wiki/index.md first.