By daymade
Verifies factual claims in documents by searching the web and authoritative sources, then proposes corrections requiring user confirmation. Useful for fact-checking AI model specs, technical documentation, statistics, and general statements.
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npx claudepluginhub p/daymade-fact-checker-fact-checkerCo-create a personal investment-research LLM Wiki (Andrej Karpathy's pattern) where the user's OWN analysis framework becomes a living CLAUDE.md — by interviewing them, NOT by handing them a template. Use whenever the user wants to build a compounding research knowledge base, 投研第二大脑, 投研知识库, or 个人投研 wiki; instantiate Karpathy's LLM Wiki gist for finance/investing; turn their stock-picking, analyst-tracking, or earnings-watching workflow into a structured markdown vault; or build a wiki tracking companies / industries / macro / analysts over time. Pure markdown + wikilinks, NO RAG / vector DB (Karpathy's core idea — do not over-engineer). Also triggers for ingesting research reports / earnings calls / expert notes into an existing wiki, and for post-earnings prediction→fulfillment reviews. Core value = extracting the user's personal investment preferences into THEIR OWN schema, never imposing a standard one.
Compare two videos and generate interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Use when analyzing compression results, evaluating codec performance, or assessing video quality differences
Generate format-controlled research reports with evidence tracking, source governance, and multi-pass synthesis. V6.1 adds: source accessibility (circular verification forbidden, exclusive advantage encouraged). Enterprise Research Mode: six-dimension data collection, SWOT/barrier/risk frameworks, and three-level quality control for company research
Scan and remove sensitive data (secrets, API keys, private domains/IPs, PII) from GitHub repository history. Use this skill whenever the user says scan sensitive data, clean git history, remove secrets from repo, sanitize GitHub history, 清理敏感数据, 历史重写, force push, 泄露, or needs to repair a public repo after accidental secret/private context leakage. Also use before any force push to a public repository to verify visibility, backup, and scan results.
Investigate and resolve Cloudflare configuration issues using API-driven evidence gathering. Use when troubleshooting ERR_TOO_MANY_REDIRECTS, SSL errors, DNS issues, or any Cloudflare-related problems
Documentation and authoring workflow router: audit docs vs code drift, sync docs after changes, optimize prompts and SKILL.md files, validate GLFM and Markdown formatting, summarize files/URLs/images with fidelity enforcement. Use when: docs are out of date, CLAUDE.md needs improving, SKILL.md needs optimizing, checking if documentation matches code, summarizing files or URLs.
Force Claude to re-validate when you have doubts (!doubt)
Documentation review, cleanup, and generation with AI slop detection, style learning, and human-quality writing enforcement
Document review skills from Draft Detective: AI-powered checks that help authors catch issues in their documents before publication.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.