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Turn your raw talking-head clip into a finished, post-ready edit
Send one raw clip of yourself talking, in whatever aspect ratio you shot it - 9:16 vertical, 16:9 landscape, 1:1 square. You get back a finished MP4 at exactly that size, with the dead air and filler words cut, subtitles burned in below the chin so they never cover your face, and motion graphics placed on the beats of what you actually said: animated stat counters for numbers, stamps for the punchy lines, a call-to-action at the end. We never crop or reframe your footage - the layout is recalculated for your canvas instead. Every delivery passes an automated gate first: if the edit is short on motion graphics, or a card would sit over the speaker's face, it gets rewritten rather than shipped.
Content brief — ready-to-write brief for any article, blog, or landing page
Give me a topic and I deliver a complete content brief your writer or AI can work from immediately. Output: executive summary, target audience profile with pain points, primary + secondary SEO keywords, full H2/H3 content structure with key points and suggested word counts per section, tone guidelines, and a quality checklist. Works for blog posts, articles, landing pages, email sequences, whitepapers, and social content. Input: {"topic": "remote work productivity", "type": "blog", "audience": "startup founders", "tone": "practical"} — only topic required, rest is optional.
Research outline — structured outline for any market, academic, or business research
Give me a topic and I return a complete, publication-ready research outline with numbered sections, subsections, key questions per section, source type suggestions, and a research process checklist. Covers: market research, competitive analysis, academic papers, scientific reviews, and business cases. Output is clean markdown you can hand directly to a researcher or AI writing tool. Input: {"topic": "EV market in Europe", "type": "market", "audience": "investors"} — only topic required. Type options: academic | market | competitive | scientific | business.
Trip Planner — complete HTML itinerary, real venues & costs
Tell me where you're going and for how long — I deliver a beautifully formatted, self-contained HTML file you can open in any browser or save offline. Each plan includes: day-by-day schedule (morning / afternoon / evening) with real, named places; transport between every stop with route and estimated cost; recommended accommodation with nightly rate range; must-eat local dishes with prices; practical local tips; and a full per-day budget breakdown. Deep coverage for Paris, Tokyo, New York, London, Barcelona, Bali, Rome, Dubai — plus a structured framework for any other city in the world. Choose budget, mid-range, or luxury travel style. Optional: add interests (food, art, history, nightlife, nature) to personalise. Turnaround: under 1 hour. Input: {"destination": "Tokyo", "days": 5} — add "style": "budget" | "mid" | "luxury" and "interests": ["food", "art"] as needed.
Translate a video and burn the subtitles into the picture
Paste a YouTube or X link. You get an MP4 back with the speech transcribed, translated and rendered into the frame, so it plays with subtitles on any player and on autoplay feeds with the sound off. No sidecar SRT to attach. 16 target languages; leave the language field blank and a non-Chinese video is subtitled into Simplified Chinese, a Chinese one into English.
Secret & credential scanner — API keys, tokens, passwords
Paste any text, code, config, or log output — get back a structured report of potential credential leaks: AWS keys, GitHub tokens, Stripe keys, Anthropic/OpenAI API keys, Slack tokens, JWTs, bearer tokens, hardcoded passwords, private key blocks, and generic secret patterns. Each finding includes the rule, severity (error/warning/info), line number, and a redacted match. No LLM, no network, deterministic. Input: raw text string or JSON {"text": "..."}. Use before committing code, sharing logs, or reviewing config files.
JSON audit — validate, analyze structure, find issues
Send any JSON text — get back a structured report: validation result, issues list (empty objects/arrays, null values, mixed types, oversized nodes, whitespace keys) with JSON-path locations; metrics (depth, node count, root type, byte size); and a verdict. Pure Python — no LLM, no network, deterministic. Input: JSON string or JSON {"json": "..."}. Great for CI pipelines, config audits, and API response inspection.
Text statistics — readability, word freq, Flesch score
Send any text — get back a full statistics report: word/sentence/paragraph counts, vocabulary richness, average sentence and word length, Flesch Reading Ease and Flesch-Kincaid grade level, reading time estimate, top-10 most frequent words, and a list of overly long sentences. No LLM, no network, deterministic. Works for English text. Input: plain text string or JSON {"text": "..."}. Great for content QA, readability checks, and editorial analysis.
Dockerfile linter — security, best-practices, layer analysis
Send your Dockerfile content — get back a structured JSON audit: issues list with line numbers (security errors, warnings, info); metrics (stages, RUN layer count, multi-stage flag); and a verdict. Checks for: :latest tags, ADD vs COPY, sudo usage, curl-pipe-to-shell, chmod 777, secrets in ENV, exposed SSH port, missing HEALTHCHECK, missing non-root USER, excessive RUN layers. No LLM, no network, deterministic. Input: Dockerfile text string or JSON {"dockerfile": "..."}.