octomind-tap

Turn raw data into a decision-ready report a human actually reads — structured by the Minto Pyramid (answer first), every number traced to the data, the right chart for each question, and delivered as a self-contained HTML document that opens in any browser and prints to clean PDF with no dependencies. Format-flexible; grounded, never fabricated.

How modern applicant tracking systems rank resumes in 2026 and how to tailor a resume per job posting so it clears them — keyword strategy grounded in the candidate's real experience, job-title placement, coverage targets, parser-safe formatting, and the anti-stuffing rules that current ATS actively penalize. Truthful tailoring only.

The dimensions of a deep code review — correctness, security, concurrency, performance, design/maintainability, tests — what each lens hunts for, and the adversarial verification discipline that keeps a multi-reviewer pass from multiplying false positives. Consensus is not correctness; every finding must be refuted before it is trusted.

Translate and localize documents, code comments, UI strings, and structured content while preserving formatting, adapting to domain-specific terminology, and maintaining consistency across large files via batching.

Write a cover letter that a hiring manager actually reads — grounded in the candidate's real experience, tailored to the specific posting and company, structured for a 30-second skim, and free of the generic AI-template phrasing that gets letters discarded. Truthful, specific, and human.

Operate the local computer's native UI — macOS, Linux, or Windows — via the desktop-automation MCP server. Covers OS accessibility / screen-recording permissions, pixel-anchor targeting (no semantic UI tree), region-capture discipline under the MCP response cap, window focus and multi-monitor handling, keyboard / mouse / clipboard sequencing, and the safety boundary around destructive desktop actions and screen-lock / biometric bypass. Activate when the user wants to drive a native desktop app or the OS shell at the GUI layer. Pairs with the device:operator agent which carries the shared snapshot → verify → record discipline; this skill carries the desktop-specific tooling and rules and pulls the device-computer capability automatically.

Production playbook for building modern lightweight landing pages that sell. Covers automatic dark/light theming via CSS custom properties, system-font Apple-style typography, opinionated section anatomy (hero, features, comparison, pricing, FAQ, footer CTA), conversion-focused copy hierarchy, SEO/OG/JSON-LD baseline, and the structural patterns that move visitors to purchase. Activate whenever drafting, designing, or implementing a marketing or product landing page.

Country-by-country conventions for job-application documents in 2026 — resume vs CV terminology, length, whether to include a photo, GDPR/consent clauses, date and locale formatting, and personal-data norms. Adapt an application to the target market so it reads correctly and stays legally safe wherever it's sent.

Deep guide for writing Octomind agent manifests: TOML format, required fields, system prompt structure, temperature guidelines, workflow/layer patterns, and the pre-write checklist. Activate when creating or editing agents/<domain>/<spec>.toml files.

Complete guide for creating AgentSkills-compliant SKILL.md packs in the octomind-tap registry: frontmatter fields, body structure, auto-activation rules, validate scripts, and quality principles. Activate when creating or editing skills/<name>/SKILL.md files.

Platform-specific intel for harvesting Bluesky trends — AT-Proto repost-driven amplification, custom-feed targeting, harvest URLs, scoring on repost-to-like ratio (no view counts), hook taxonomy tuned to Bluesky's technical / anti-marketing audience, and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names Bluesky.

Platform-specific intel for harvesting Hacker News trends — point-velocity ranking, harvest URLs (front page, new, Show, Ask, Algolia), flag-tax mechanics, title rules from HN guidelines, Show HN / Ask HN / link-submission patterns, anchor commenters and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names HN / Hacker News.

Platform-specific intel for harvesting LinkedIn trends — dwell-and-comment ranking signals, harvest URLs, scoring on comment-to-reaction ratio and reshare-with-commentary, hook taxonomy that earns the 210-char expand-click in 2026, format-mix shifts (carousel rising / video / text), and dead patterns. Activates inside an octoweb:trend session whenever the user names LinkedIn.

Platform-specific intel for harvesting Mastodon trends across federation — boost-driven amplification, per-instance culture map, hashtag-following discovery, harvest URLs across home + niche instances, content-warning conventions, alt-text expectations, and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names Mastodon.

Platform-specific intel for harvesting Reddit trends across niche subreddits — upvote-velocity ranking, harvest URLs per-sub (hot/rising/top/new), mod-rules pre-flight that prevents removed posts, per-sub culture map for tech / AI / startup niches, title patterns and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names Reddit.

Platform-specific intel for harvesting Threads trends — current conversation-weighted ranking signals, harvest URLs, scoring rubric using reply-to-like ratio and author-reply density (views aren't surfaced), hook taxonomy that's currently winning, and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names Threads.

Platform-specific intel for harvesting X (Twitter) trends — current ranking mechanisms verified against the open-sourced Phoenix For You algorithm (Banger Initial Screen / slop classifier, predicted-action scoring incl. negative-weighted scroll-past, per-feed author diversity decay, mutual-follow Jaccard as ranking input, 7 PTOS kill-switches, sticky hash embeddings, video duration floor), harvest URLs with min_faves/min_retweets filters, scoring rubric on view ratios, hook taxonomy that's currently winning, and dead patterns the algorithm suppresses. Activates inside an octoweb:trend session whenever the user names X / Twitter.

One-line description of what this skill does and when to use it. Be specific — this is what the AI reads when deciding whether to activate the skill.

Science of AI text detection, 8-dimension humanization diagnostic, and 7-pass rewrite technique for transforming AI-generated content into genuinely human writing.

Per-language calibration anchors for detecting AI-slop and translationese in Arabic (ar) target text — auto-loads alongside content-locale-humanize when the target language is Arabic.

Per-language calibration anchors for detecting AI-slop and translationese in German (de) target text — auto-loads alongside content-locale-humanize when the target language is German.

Per-language calibration anchors for detecting AI-slop and translationese in Spanish (es) target text — auto-loads alongside content-locale-humanize when the target language is Spanish.

Per-language calibration anchors for detecting AI-slop and translationese in French (fr) target text — auto-loads alongside content-locale-humanize when the target language is French.

Per-language calibration anchors for detecting AI-slop and translationese in Hindi (hi) target text — auto-loads alongside content-locale-humanize when the target language is Hindi.

Per-language calibration anchors for detecting AI-slop and translationese in Italian (it) target text — auto-loads alongside content-locale-humanize when the target language is Italian.

Per-language calibration anchors for detecting AI-slop and translationese in Japanese (ja) target text — auto-loads alongside content-locale-humanize when the target language is Japanese.

Per-language calibration anchors for detecting AI-slop and translationese in Korean (ko) target text — auto-loads alongside content-locale-humanize when the target language is Korean.

Per-language calibration anchors for detecting AI-slop and translationese in Portuguese (pt) target text — auto-loads alongside content-locale-humanize when the target language is Portuguese.

MQM-informed, structural-pattern diagnostic for making translated/localized content read as if a native speaker wrote it from scratch, in any target language — detects translationese and AI-slop by pattern (interference, frequency outliers, rhythm, templating), not by a per-language word list.

Per-language calibration anchors for detecting AI-slop and translationese in Thai (th) target text — auto-loads alongside content-locale-humanize when the target language is Thai.

Per-language calibration anchors for detecting AI-slop and translationese in Chinese (zh) target text — auto-loads alongside content-locale-humanize when the target language is Chinese.

AI pattern avoidance, dead vocabulary, voice rules, and rhythm guidance for writing that reads as genuinely human. Apply to any content writing or rewriting task.

The universal coaching method any coach agent runs: GROW, ICF active listening, powerful (non-leading) questions, goal-setting with WOOP and if-then plans, and accountability design. Activate when coaching someone toward a goal, running a 1:1, or designing follow-through — and when you catch yourself dispensing advice instead of drawing the answer out.

The small set of evidence-based study techniques that actually work — retrieval practice, spacing, interleaving, the Feynman technique, and worked examples — and the popular habits (rereading, highlighting, cramming, learning styles) that only feel productive. Activate when helping someone study, memorize, prepare for a test, or learn a skill, or when they ask how to learn something faster.

Complete guide for octomind workflow files — pipeline design (pattern selection, step decomposition, sentinel handoff contracts, loop convergence, context economics) plus the exact TOML syntax for the external orchestrator that chains octomind run subprocesses. Covers sequential/parallel/loop/conditional steps, variable substitution, session modes, pre-flight validation, and the CLI. Activate when designing, authoring, validating, or debugging a workflow .toml file.

Ground-truth 2026 playbook for posting, commenting, and replying on Reddit. Covers the ranking algorithm, subreddit-first research, the 90/10 self-promotion rule, title craft, post body structure, comment strategy, thread-vibe matching, and surviving AI-content automods. Replies and comments must read as a real human typed them — imperfect, thread-aware, naturally flawed. Activate whenever drafting anything destined for Reddit.

What to produce for a Microsoft Advertising creative — Responsive Search Ads (RSA with Microsoft-only long headlines), Multimedia Ads, Audience Ads (Outlook.com / MSN / Microsoft Start / Edge News), Performance Max, Shopping, Lodging/Travel verticals, Video, and Connected TV (Netflix inventory via Microsoft Invest / Xandr). Encodes the exact slots, char limits (including Microsoft's 90-char long-headline slot that Google does NOT have), asset ratios, CTA enum, LinkedIn Profile Targeting note, Copilot creative behavior, and the trademark/political/regional policy differences from Google. Use whenever the task is producing Microsoft Ads / Bing copy or assets. Strictly platform-specific — does not cover keyword strategy, bidding, audience setup, or UET pixel.

What to produce for a Google Ads creative — Search RSA, Performance Max, and Display. Encodes the exact slots (headlines, descriptions, paths, long headline, long description), character limits, pinning rules, asset ratios, and policy constraints so copy fits before it's pasted into Google Ads Editor. Use whenever the task is producing Google Ads ad copy or assets. Strictly platform-specific — does not cover bidding, keywords selection, audience setup, or attribution.

What to produce for a LinkedIn ad — Sponsored Content (single image, video, carousel, document), Message Ads, and Text Ads. Encodes the exact slots (intro text, headline, description), character limits, asset ratios, the CTA enum per format, and the professional-context rules that decide whether B2B audiences engage or scroll past. Use whenever the task is producing LinkedIn ad copy or asset briefs. Strictly platform-specific — does not cover audience filters, matched audiences, or LinkedIn Insight Tag setup.

What to produce for a Meta ad — Facebook Feed, Instagram Feed, Stories, Reels, and the CTA enum. Encodes the exact slots (primary text, headline, description, CTA button), character limits, asset ratios (1:1, 4:5, 9:16), policy filters, and the truncation behavior that decides whether anyone reads past the fold. Use whenever the task is producing Meta ad copy or asset briefs. Strictly platform-specific — does not cover audience setup, pixel events, or campaign objectives.