PAI_Silenced

Generates static visual content across 20+ formats via Flux, Nano Banana Pro (Gemini 3 Pro), and GPT-Image-1. Covers blog header illustrations, editorial art, Mermaid flowcharts, technical architecture diagrams, D3.js dashboards, taxonomies, timelines, 2x2 framework matrices, comparisons, annotated screenshots, recipe cards, aphorism/quote cards, conceptual maps, stat cards, comic panels, YouTube thumbnails, PAI pack icons, and brand-logo wallpapers. Named workflows: Essay, D3Dashboards, Visualize, Mermaid, TechnicalDiagrams, Taxonomies, Timelines, Frameworks, Comparisons, AnnotatedScreenshots, RecipeCards, Aphorisms, Maps, Stats, Comics, YouTubeThumbnailChecklist, AdHocYouTubeThumbnail, CreatePAIPackIcon, LogoWallpaper, RemoveBackground. SKILLCUSTOMIZATIONS loads PREFERENCES.md, CharacterSpecs.md, and SceneConstruction.md. --remove-bg flag produces transparent-background PNG (can produce black backgrounds — verify visually). Up to 14 reference images per request (5 human, 6 object Gemini API limit). Output s

Generate illustrations, technical diagrams, mermaid flowcharts, infographics, header images, thumbnails, comics, and PAI pack icons using multiple rendering backends. USE WHEN art, header images, visualizations, mermaid, flowchart, technical diagram, infographic, PAI icon, pack icon, YouTube thumbnails, ad hoc thumbnails, annotated screenshots, aphorisms, comics, comparisons, D3 dashboards, embossed logo wallpaper, essay illustration, frameworks, maps, recipe cards, remove background, stats, taxonomies, timelines, brand wallpaper, visualize, generate image, Midjourney, compose thumbnail, generate prompt.

Visual and video content creation — illustrations, diagrams, mermaid flowcharts, infographics, header images, PAI pack icons, thumbnails, comics, and programmatic video via Remotion. USE WHEN art, header images, visualizations, mermaid, diagrams, flowcharts, infographics, pack icons, video, animation, motion graphics, Remotion, video rendering, YouTube thumbnails, comics, comparisons, frameworks, maps, timelines, taxonomies, stats, aphorisms, recipe cards, annotated screenshots, D3 dashboards, embossed logo wallpaper, remove background, essay illustration, technical diagrams, content to animation, generate image, Midjourney.

Generate prioritized PAI upgrade recommendations via 4 parallel threads: Thread 0 (prior-work audit — reads current Algorithm, PATTERNS.yaml, hooks, settings, recent ISAs, and KNOWLEDGE to assign Prior Status tags), Thread 1 (user context — TELOS goals, active projects, PAI system state), Thread 2 (source collection — Anthropic releases, YouTube channels, GitHub trending, custom sources), Thread 3 (internal reflections — Algorithm execution Q1/Q2 patterns). Output format: Discoveries table ranked by interestingness, then tiered Recommendations (CRITICAL/HIGH/MEDIUM/LOW) each with Prior Status (NEW/PARTIAL/DISCUSSED/REJECTED/DONE), then full Technique Details with before/after code. Every recommendation cites file:line evidence from Thread 0 — already-implemented items go to Skipped, never re-surfaced. Workflows: Upgrade, MineReflections, AlgorithmUpgrade, ResearchUpgrade, FindSources, TwitterBookmarks. USE WHEN upgrade, system upgrade, check Anthropic, new Claude features, algorithm upgrade, PAI upgrade, chec

Extract system improvements from content AND monitor external sources (Anthropic ecosystem, YouTube). USE WHEN upgrade, improve system, system upgrade, analyze for improvements, check Anthropic, Anthropic changes, new Claude features, check YouTube, new videos, algorithm upgrade, mine reflections, find sources, research upgrade, PAI upgrade.

Developer utilities and tools — CLI generation, skill scaffolding, agent delegation, system upgrades, evals, documents, parsing, audio editing, Fabric patterns, Cloudflare infrastructure, browser automation, meta-prompting, and aphorisms. USE WHEN create CLI, build CLI, command-line tool, wrap API, add command, upgrade tier, TypeScript CLI, create skill, new skill, scaffold skill, validate skill, update skill, fix skill structure, canonicalize skill, parallel execution, agent teams, delegate, workstreams, swarm, upgrade, improve system, system upgrade, check Anthropic, algorithm upgrade, mine reflections, find sources, research upgrade, PAI upgrade, eval, evaluate, test agent, benchmark, verify behavior, regression test, capability test, run eval, compare models, compare prompts, create judge, view results, document, process file, create document, convert format, extract text, PDF, DOCX, XLSX, PPTX, Word, Excel, spreadsheet, PowerPoint, presentation, slides, consulting report, large PDF, merge PDF, fill form,

Compose CUSTOM agents from Base Traits + Voice + Specialization, and manage predefined functional TEAMS. Traits combine expertise (security, technical, research), personality (skeptical, analytical, enthusiastic), and approach (thorough, rapid, systematic). ComposeAgent.ts merges base + user config, outputs unique prompt + ElevenLabs voice + prosody. Predefined teams: engineering, architecture, marketing, design, security, research, content, strategy — each YAML-configured with roles, tensions, and specialist members. Observer team variant: read-only oversight agents that vote continue/halt/escalate against the tool-activity audit log (high-blast-radius or unattended runs only). USE WHEN create custom agents, spin up agents, specialized agents, agent personalities, available traits, list traits, agent voices, compose agent, spawn parallel agents, launch agents, engineering team, architecture team, marketing team, design team, security team, research team, content team, strategy team, get the team on this, obs

Scrape social media platforms, business data, and e-commerce via Apify actors — Instagram profiles/posts/hashtags/comments, LinkedIn profiles/jobs/posts, TikTok profiles/hashtags/videos/comments, YouTube channels/search/comments, Facebook posts/groups/comments, Google Maps business search with contact/review/image extraction, Amazon products/reviews/pricing, and general-purpose multi-page web crawling with custom pageFunction extraction logic. File-based TypeScript wrappers (scrapeInstagramProfile, searchGoogleMaps, scrapeAmazonProduct, scrapeWebsite, etc.) filter and transform data in code before returning to model context, achieving 95-99% token savings over direct MCP protocol. Parallel multi-platform queries via Promise.all for social listening dashboards. Lead enrichment pipeline: Google Maps → qualified filter → optional LinkedIn enrichment. Competitive analysis across Instagram, YouTube, and TikTok simultaneously. USE WHEN scrape Instagram, scrape LinkedIn, scrape TikTok, scrape YouTube, scrape Faceboo

Generates static visual content across 20+ formats via Flux, Nano Banana Pro (Gemini 3 Pro), and GPT-Image-1. Covers blog header illustrations, editorial art, Mermaid flowcharts, technical architecture diagrams, D3.js dashboards, taxonomies, timelines, 2x2 framework matrices, comparisons, annotated screenshots, recipe cards, aphorism/quote cards, conceptual maps, stat cards, comic panels, YouTube thumbnails, PAI pack icons, and brand-logo wallpapers. Named workflows: Essay, D3Dashboards, Visualize, Mermaid, TechnicalDiagrams, Taxonomies, Timelines, Frameworks, Comparisons, AnnotatedScreenshots, RecipeCards, Aphorisms, Maps, Stats, Comics, YouTubeThumbnailChecklist, AdHocYouTubeThumbnail, CreatePAIPackIcon, LogoWallpaper, RemoveBackground. SKILLCUSTOMIZATIONS loads PREFERENCES.md, CharacterSpecs.md, and SceneConstruction.md. --remove-bg flag produces transparent-background PNG (can produce black backgrounds — verify visually). Up to 14 reference images per request (5 human, 6 object Gemini API limit). Output s

AI-powered audio and video editing pipeline: Whisper word-level transcription (insanely-fast-whisper on MPS) → Claude segment classification (KEEP / CUT_FILLER / CUT_FALSE_START / CUT_STUTTER / CUT_DEAD_AIR / CUT_EDIT_MARKER) → ffmpeg execution with 40ms qsin crossfades and room-tone gap fill → optional Cleanvoice API cloud polish for mouth sounds and loudness normalization. Distinguishes rhetorical pauses from accidental ones. Breaths attenuated to 50% volume (not removed). Preview mode (--preview flag) shows proposed cuts without modifying audio. Aggressive mode (--aggressive flag) applies tighter filler detection thresholds. Polish step (--polish flag) uploads to Cleanvoice API for mouth sound removal and loudness normalization — confirm before cloud upload of sensitive content. Pipeline tools: Transcribe.ts, Analyze.ts, Edit.ts, Polish.ts, Pipeline.ts. Single workflow: Clean.md. Requires ANTHROPIC_API_KEY; CLEANVOICE_API_KEY optional for polish step. USE WHEN: clean audio, edit audio, remove filler words,

2-phase context search across the PAI session registry, work directories, and ISAs for instant cold-start recovery. Phase 1 (always): parallel scan of work.json session registry, session-names.json, MEMORY/WORK/ directory names, and ISA title grep — returns 5 most recent matches per source, loads top-3 ISA summaries (first 10 lines only). Phase 2 (only if Phase 1 returns fewer than 3 matches): PAI git history + current project git history. Output: compact context block under 40 lines with session slugs, phases, progress, and ISA paths. Reads MEMORY/STATE/work.json (task, phase, progress, effort) and MEMORY/STATE/session-names.json (sessionId, name); uses fd for directory scan with --max-depth 1 and Grep for ISA title matches in files_with_matches mode. Git history searched via `git log --oneline --all --grep` on both PAI and current project repo. Output: session slugs (newest first), ISA summaries (first 10 lines), commit hashes if Phase 2 ran. Standalone mode: present results then ask what to do. Paired mode

Manage the public daemon profile — a living digital representation of what you're working on, thinking about, reading, and building. DaemonAggregator.ts reads PAI sources (TELOS missions/goals/books/wisdom, KNOWLEDGE/Ideas titles, PROJECTS.md, MEMORY/WORK themes, PRINCIPAL_IDENTITY bio) and writes to daemon-data.json. SecurityFilter.ts applies deterministic pattern-matching (NOT LLM judgment) to strip names, paths, credentials, and internal refs. Structurally excludes CONTACTS, FINANCES, HEALTH, OUR_STORY, OPINIONS. deploy.sh builds the VitePress static site and deploys to Cloudflare Pages. Two-repo pattern: public framework (danielmiessler/Daemon, forkable) + private content (daemon-dm). Workflows: UpdateDaemon, ReadDaemon, PreviewDaemon, DeployDaemon. USE WHEN daemon, update daemon, daemon profile, deploy daemon, preview daemon, read daemon, check daemon, daemon status, public profile, digital presence. NOT FOR internal PAI system management (use _PAI).

Comprehensive AI agent evaluation framework with three grader types (code-based: deterministic/fast; model-based: nuanced/LLM rubric; human: gold standard) and pass@k / pass^k scoring. Evaluates agent transcripts, tool-call sequences, and multi-turn conversations — not just single outputs. Supports capability evals (~70% pass target) and regression evals (~99% pass target). Workflows: RunEval, CompareModels, ComparePrompts, CreateJudge, CreateUseCase, RunScenario, CreateScenario, ViewResults. Integrates with THE ALGORITHM ISC rows for automated verification. Domain patterns pre-configured for coding, conversational, research, and computer-use agent types in Data/DomainPatterns.yaml. Tools: AlgorithmBridge.ts (ISC integration), FailureToTask.ts (failures → tasks), SuiteManager.ts (create/graduate/saturation-check), ScenarioRunner.ts (multi-turn simulated-user), TranscriptCapture.ts, PAIAgentAdapter.ts (wraps Inference.ts), ScenarioToTranscript.ts. Code-based graders: string_match, regex_match, binary_tests, st

Generate prioritized PAI upgrade recommendations via 4 parallel threads: Thread 0 (prior-work audit — reads current Algorithm, PATTERNS.yaml, hooks, settings, recent ISAs, and KNOWLEDGE to assign Prior Status tags), Thread 1 (user context — TELOS goals, active projects, PAI system state), Thread 2 (source collection — Anthropic releases, YouTube channels, GitHub trending, custom sources), Thread 3 (internal reflections — Algorithm execution Q1/Q2 patterns). Output format: Discoveries table ranked by interestingness, then tiered Recommendations (CRITICAL/HIGH/MEDIUM/LOW) each with Prior Status (NEW/PARTIAL/DISCUSSED/REJECTED/DONE), then full Technique Details with before/after code. Every recommendation cites file:line evidence from Thread 0 — already-implemented items go to Skipped, never re-surfaced. Workflows: Upgrade, MineReflections, AlgorithmUpgrade, ResearchUpgrade, FindSources, TwitterBookmarks. USE WHEN upgrade, system upgrade, check Anthropic, new Claude features, algorithm upgrade, PAI upgrade, chec

Meta-prompting standard library — the PAI system for generating, optimizing, and composing prompts programmatically. Owns three pillars: Standards (Anthropic Claude 4.x best practices, context engineering principles, 1,500+ paper synthesis, Fabric pattern system, markdown-first / no-XML-tags); Templates (Handlebars-based — Briefing.hbs, Structure.hbs, Gate.hbs, DynamicAgent.hbs, and eval-specific templates Judge.hbs, Rubric.hbs, TestCase.hbs, Comparison.hbs, Report.hbs used by Agents and Evals skills); and Tools (RenderTemplate.ts for CLI/TypeScript rendering with data-content separation). Philosophy: prompts that write prompts — structure is code, content is data. Delivered 65% token reduction across PAI (53K → 18K tokens) via template extraction. Output is always a prompt to be used elsewhere, not final content. Reference files: Standards.md (complete prompt engineering guide), Tools/RenderTemplate.ts (rendering implementation). NOT FOR generating final content or answers — this skill produces prompts only

Comprehensive research and content extraction with 4 depth modes: Quick (1 Perplexity agent, ~10-15s), Standard (4 agents — Claude + Gemini + Grok + Perplexity, cross-checked, ~30-60s), Extensive (7 explorers + 2 independent verifiers, ~60-90s), Deep Investigation (progressive iteration with persistent MEMORY/RESEARCH/ vault, loop-compatible, ~3-60min). Every URL verified before delivery — hallucinated links are a catastrophic failure. Verification architecture: per-agent self-verification, cross-check synthesis, and independent verifier agents (Extensive/Deep). Confidence-tagged output: [HIGH] [MED] [LOW] [CONFLICT]. Additional workflows: ExtractAlpha (highest-signal insights), Retrieve (CAPTCHA/bot-blocked content), YoutubeExtraction (fabric -y), WebScraping, InterviewResearch (Tyler Cowen style), AnalyzeAiTrends, Fabric (242+ patterns), Enhance, ExtractKnowledge. USE WHEN research, do research, quick research, extensive research, deep investigation, find information, investigate, extract alpha, analyze con

Dual-context Life OS and organizational analysis skill. Personal TELOS: read and update goals, beliefs, wisdom, books, movies, challenges, narratives, strategies, mission, mental models, predictions, traumas, frames, lessons-learned, and wrong-beliefs stored in the USER/TELOS/ directory — all via the Update workflow with timestamped backups and change logging. Valid personal files: BELIEFS.md, BOOKS.md, CHALLENGES.md, FRAMES.md, GOALS.md, LEARNED.md, MISSION.md, MODELS.md, MOVIES.md, NARRATIVES.md, PREDICTIONS.md, PROBLEMS.md, PROJECTS.md, STRATEGIES.md, TELOS.md, TRAUMAS.md, WISDOM.md, WRONG.md. Project TELOS: analyze any directory of .md/.csv files to extract relationships, dependency chains (PROBLEMS→GOALS→STRATEGIES→PROJECTS), bottlenecks, goal alignment, and progress metrics; generate McKinsey-style professional reports (WriteReport) or n=24 slide-ready narrative bullet points (CreateNarrativePoints); build interactive Next.js 14 + shadcn/ui + Aceternity + Recharts + D3.js dashboards via up to 16 paralle

Analyze and update 68 US economic and social indicators from five government APIs: FRED, EIA, Treasury FiscalData, BLS, Census. Ten categories: Economic Output & Growth (GDP, industrial production, retail sales), Inflation & Prices (CPI, PCE, gas, oil), Employment & Labor (unemployment, payrolls, jobless claims, quit rate), Housing (home prices, mortgage rates, starts), Consumer & Personal Finance (sentiment, saving rate, credit), Financial Markets (interest rates, Treasury yields, volatility), Trade & International (trade balance, USD index), Government & Fiscal (federal debt, deficit, spending), Demographics & Social (population, inequality, poverty), Health & Crisis (deaths of despair, air quality, life expectancy). Two workflows: UpdateData (fetch live data via FRED_API_KEY and EIA_API_KEY, update US-Common-Metrics.md, us-metrics-current.csv, us-metrics-historical.csv in Substrate dataset), GetCurrentState (10y/5y/2y/1y multi-timeframe trend analysis, cross-category correlation, pattern/anomaly detection,

Design and integrate web interfaces using Anthropic's Claude Design (claude.ai/design) as the primary engine, with optional downstream handoff to the frontend-design plugin for production code. Drives Claude Design through the Interceptor skill for programmatic access to the authenticated claude.ai session. USE WHEN: web design, UI design, create prototype, design system, design tokens, brand extraction, redesign site, mockup, wireframe, landing page, dashboard design, component library, design-to-code, figma alternative, claude design, frontend design, polish UI, design audit, accessibility review. ALSO USE WHEN: this skill is called as a sub-step of larger site work (blog, admin panel, marketing site) — it integrates designs INTO an existing application, not just greenfield. NOT FOR: static illustrations or diagrams (use Art), logo/brand asset generation (use Art), video/motion graphics (use Remotion), or arbitrary graphic design outside the web/UI domain.

Compose CUSTOM agents from Base Traits + Voice + Specialization for specialized perspectives. USE WHEN create custom agents, spin up agents, specialized agents, agent personalities, available traits, list traits, agent voices, compose agent, load agent context, agent profile, spawn parallel agents, launch agents. NOT for agent teams/swarms (use Delegation skill → TeamCreate).

3-pass scope oscillation that holds a question constant while shifting the scope envelope — narrow/tactical, wide/strategic, then synthesis — to surface design tensions invisible at any single zoom level. Requires two distinct inputs: the tactical target (what you're building) and strategic context (the larger system it serves). Pass 1 captures the component's own internal logic. Pass 2 reveals what the system needs it to be. Pass 3 finds where those views diverge — that delta is the output. Produces: design tensions, scope recommendations, and coherence assessments. Single workflow: Workflows/Oscillate.md. BPE-fragile — quarterly test recommended to verify smarter models don't naturally oscillate scope without prompting. Best integration point: Algorithm OBSERVE phase (before ISC) or THINK phase (before approach commitment). NOT a lens rotation (that's IterativeDepth) and NOT idea generation (that's BeCreative). NOT FOR deep incident causal chains (use RootCauseAnalysis) or assumption decomposition (use Firs

Manages a curated aphorism collection with full CRUD — content-based matching, themed search, thinker research, and database maintenance. Organizes quotes by author, theme, context, and newsletter usage history to prevent repetition. Four workflows: FindAphorism (analyze newsletter content, match themes, return 3-5 ranked recommendations with rationale), AddAphorism (parse quote + author, extract themes, validate uniqueness, update theme index), ResearchThinker (deep research on philosopher, add sourced quotes to database), SearchAphorisms (search by theme, keyword, or author). Database at ~/.claude/skills/aphorisms/Database/aphorisms.md — stores full quote text, author attribution, theme tags, context/background, source reference, and usage history per entry. Theme index supports 12+ categories: Work Ethic, Resilience, Learning, Stoicism, Risk, Wisdom, Truth-seeking, Excellence, Curiosity, Freedom, Rationality, Clarity. Supported thinkers: Hitchens, Feynman, Deutsch, Sam Harris, Spinoza, plus any requested a

Scrape social media platforms, business data, and e-commerce via Apify actors — Instagram profiles/posts/hashtags/comments, LinkedIn profiles/jobs/posts, TikTok profiles/hashtags/videos/comments, YouTube channels/search/comments, Facebook posts/groups/comments, Google Maps business search with contact/review/image extraction, Amazon products/reviews/pricing, and general-purpose multi-page web crawling with custom pageFunction extraction logic. File-based TypeScript wrappers (scrapeInstagramProfile, searchGoogleMaps, scrapeAmazonProduct, scrapeWebsite, etc.) filter and transform data in code before returning to model context, achieving 95-99% token savings over direct MCP protocol. Parallel multi-platform queries via Promise.all for social listening dashboards. Lead enrichment pipeline: Google Maps → qualified filter → optional LinkedIn enrichment. Competitive analysis across Instagram, YouTube, and TikTok simultaneously. USE WHEN scrape Instagram, scrape LinkedIn, scrape TikTok, scrape YouTube, scrape Faceboo

Divergent ideation and corpus expansion using Verbalized Sampling + extended thinking. Single-shot mode generates 5 internally diverse candidates (p<0.10 each) and surfaces the strongest. Multi-turn mode expands a small seed corpus (5-20 examples) into a diverse N-example dataset for evals, training, or test sets. Research-backed: Zhang et al. 2025 (arXiv:2510.01171) — 1.6-2.1x diversity increase on creative writing, 25.7% quality improvement, and synthetic-data downstream accuracy lift 30.6% → 37.5% on math benchmarks. Seven workflows: StandardCreativity, MaximumCreativity, IdeaGeneration, TreeOfThoughts, DomainSpecific, TechnicalCreativityGemini3 for algorithmic/architecture work, and SyntheticDataExpansion for VS-Multi corpus growth. Single-shot output is one best response, not a ranked list; SyntheticDataExpansion writes a JSONL corpus to MEMORY/WORK/{slug}/synthetic-data/. Integrates with XPost, LinkedInPost, Blogging (creative angles), Art (diverse image prompt ideas), Business (offer frameworks), Resea

4-tier progressive scraping with automatic escalation: Tier 1 WebFetch (fast, built-in), Tier 2 curl with Chrome headers (basic bot bypass), Tier 3 agent-browser (headless JavaScript rendering via Rust CLI daemon), Tier 4 Bright Data MCP proxy (CAPTCHA, advanced bot detection, residential proxies). Two workflows: FourTierScrape for single URLs, Crawl for multi-page site mapping (light crawl via scrape_batch loop up to 50 pages, or full crawl via Bright Data Crawl API). Always starts at Tier 1 and escalates only when blocked — Tier 4 has usage costs. Outputs URL content in markdown format. USE WHEN Bright Data, scrape URL, web scraping, bot detection, crawl site, CAPTCHA, can't access, site blocking, extract page content, scrape whole site, spider domain, convert URL to markdown, getting blocked. NOT FOR headless batch automation without scraping need (use Browser). NOT FOR simple public content (use WebFetch directly). NOT FOR real-browser bot bypass where staying logged in and zero CDP fingerprint matter (us

Generate production-ready TypeScript CLIs using a 3-tier template system: Tier 1 llcli-style manual arg parsing (zero deps, Bun + TypeScript, ~300-400 lines — 80% of cases), Tier 2 Commander.js (subcommands, nested options, auto-help — 15%), Tier 3 oclif reference only (enterprise scale — 5%). Every generated CLI includes full implementation, README + QUICKSTART docs, package.json with Bun, tsconfig strict mode, type-safe throughout, JSON output, exit code compliance. Workflows: CreateCli (from scratch), AddCommand (extend existing), UpgradeTier (migrate Tier 1 → 2). Outputs go to ~/.claude/Bin/ or ~/Projects/. Tier 1 (llcli pattern — 327 lines, zero deps) suits API clients, data transformers, simple automation — 2-10 commands, JSON output. Tier 2 (Commander.js) for 10+ commands, nested options, or plugin architecture. Tier 3 (oclif) is documentation-only reference for Heroku/Salesforce scale. Output tree: {name}.ts + package.json + tsconfig.json (strict) + .env.example + README.md + QUICKSTART.md. Quality ga

Complete PAI skill development lifecycle across two tracks. Structure track: scaffold new skills (TitleCase dirs, flat 2-level max, Workflows/ + Tools/ + References/ only), validate against canonical format, canonicalize existing skills. Effectiveness track (Anthropic methodology): TestSkill spawns with-skill vs baseline agents in parallel and compares outputs, ImproveSkill diagnoses root causes and rewrites instructions with reasoning over rigid constraints, OptimizeDescription generates 20 should/shouldn't-trigger test queries and rewrites for accuracy. Guides from Thariq Shihipar (Mar 2026): Gotchas section mandatory, BPE check before finalizing, progressive disclosure (frontmatter → SKILL.md body → reference files), on-demand hooks. USE WHEN create skill, new skill, validate skill, test skill, improve skill, optimize description, skill not triggering, skill overtriggering, canonicalize, scaffold skill, skill quality. NOT FOR TypeScript CLI generation (use CreateCLI).

Parallelize work via six patterns: built-in agents (Engineer/Architect/Algorithm/Explore/Plan via Task), worktree-isolated agents (conflict-free parallel file edits), background agents (run_in_background: true, non-blocking), custom agents (ComposeAgent via Agents skill → Task general-purpose), agent teams (TeamCreate + TaskCreate + SendMessage for multi-turn peer coordination), and parallel task dispatch (N identical operations). Two-tier delegation: lightweight (haiku, max_turns=3, one-shot extraction/classification) vs full (multi-step, tool use, iteration). Decision rule — agents need to talk to each other or share state → Teams; independent one-shot work → Subagents. Auto-invoked by Algorithm when 3+ independent workstreams exist at Extended+ effort. USE WHEN 3+ workstreams, parallel execution, agent specialization, agent team, swarm, spawn agents, create team, fan out, divide and conquer, multi-agent, coordinate agents. NOT FOR single-agent custom personality composition (use Agents skill).

Comprehensive AI agent evaluation framework with three grader types (code-based: deterministic/fast; model-based: nuanced/LLM rubric; human: gold standard) and pass@k / pass^k scoring. Evaluates agent transcripts, tool-call sequences, and multi-turn conversations — not just single outputs. Supports capability evals (~70% pass target) and regression evals (~99% pass target). Workflows: RunEval, CompareModels, ComparePrompts, CreateJudge, CreateUseCase, RunScenario, CreateScenario, ViewResults. Integrates with THE ALGORITHM ISC rows for automated verification. Domain patterns pre-configured for coding, conversational, research, and computer-use agent types in Data/DomainPatterns.yaml. Tools: AlgorithmBridge.ts (ISC integration), FailureToTask.ts (failures → tasks), SuiteManager.ts (create/graduate/saturation-check), ScenarioRunner.ts (multi-turn simulated-user), TranscriptCapture.ts, PAIAgentAdapter.ts (wraps Inference.ts), ScenarioToTranscript.ts. Code-based graders: string_match, regex_match, binary_tests, st

Execute any of 240+ specialized prompt patterns natively (no CLI required for most) across categories: Extraction (30+), Summarization (20+), Analysis (35+), Creation (50+), Improvement (10+), Security (15), Rating (8). Common patterns: extract_wisdom, summarize, create_5_sentence_summary, create_threat_model, create_stride_threat_model, analyze_claims, improve_writing, review_code, extract_main_idea, analyze_malware, create_sigma_rules, create_mermaid_visualization, youtube_summary, judge_output, rate_ai_response. Native execution reads Patterns/{name}/system.md and applies directly. Fabric CLI used only for YouTube transcript extraction (-y URL) and fallback URL fetching (-u URL). Patterns auto-synced from upstream Fabric repo via UpdatePatterns workflow. Workflows: ExecutePattern, UpdatePatterns. USE WHEN fabric, fabric pattern, run fabric, sync fabric, update patterns, use extract_wisdom, threat model, summarize, analyze claims, improve writing, review code, create prd, rate content, create diagram, merma

Physics-based reasoning framework (Musk/Elon methodology) that deconstructs problems to irreducible fundamental truths rather than reasoning by analogy. Three-step structure: DECONSTRUCT (break to constituent parts and actual values), CHALLENGE (classify every element as hard constraint / soft constraint / unvalidated assumption — only physics is truly immutable), RECONSTRUCT (build optimal solution from fundamentals alone, ignoring inherited form). Outputs: constituent-parts breakdown, constraint classification table, and reconstructed solution with key insight. Three workflows: Deconstruct.md, Challenge.md, Reconstruct.md. Integrates with RedTeam (attack assumptions before deploying adversarial agents), Security (decompose threat model), Architecture (challenge design constraints), and Pentesters (decompose assumed security boundaries). Other skills invoke via: Challenge on all stated constraints → classify as hard/soft/assumption. Cross-domain synthesis: solutions from unrelated fields often apply once the

Runs a phased conversational interview across all PAI context files using InterviewScan.ts, which orders targets by PHASE and assigns conversation mode per file. Phase 1 (foundational TELOS) always runs first regardless of completeness: MISSION, GOALS, PROBLEMS, STRATEGIES, CHALLENGES, NARRATIVES, SPARKS, BELIEFS, WISDOM, MODELS, FRAMES in leverage order. Phase 2: IDEAL_STATE (HEALTH, MONEY, FREEDOM, RELATIONSHIPS, CREATIVE) in Fill mode. Phase 3: preferences (BOOKS, AUTHORS, BANDS, MOVIES, RESTAURANTS, FOOD_PREFERENCES, LEARNING, MEETUPS, CIVIC) in mixed mode. Phase 4: light touch on CURRENT_STATE/SNAPSHOT and PRINCIPAL_IDENTITY. Phase 9 (RHYTHMS) deferred. Review mode (≥80%) reads file then asks targeted questions one at a time — still accurate, outdated, missing, sharpen? Fill mode (<80%) walks scanner prompts one at a time. The principal answers in natural language; the DA formats into file structure. Voice confirms on actual changes only. Stop signals respected immediately. Target vs. north-star type con

Structured OSINT investigations — people lookup, company intel, investment due diligence, entity/threat intel, domain recon, organization research using public sources with ethical authorization framework. USE WHEN OSINT, due diligence, background check, research person, company intel, investigate, company lookup, domain lookup, entity lookup, organization lookup, threat intel, discover OSINT sources.

Ethical people-finding using 15 parallel research agents (45 search threads) across public records, social media, reverse lookups. Public data only, no pretexting. USE WHEN find person, locate, reconnect, people search, skip trace, reverse lookup, social media search, public records search, verify identity.

OSINT and people-finding — structured investigations, company intel, due diligence, and ethical people search across public records and social media. USE WHEN OSINT, due diligence, company intel, background check, find person, locate, people search, reconnect, public records, reverse lookup, social media search, verify identity, domain lookup, entity lookup, organization lookup, company lookup, threat intel.

Owns the Ideal State Artifact — the universal primitive that holds the articulated ideal state of any thing (project, task, application, library, infrastructure, work session) as a hard-to-vary explanation. The ISA is a single document that articulates the ideal state, drives the build, verifies the build, and records the evolution of understanding. Five workflows: Scaffold (generate a fresh ISA from a prompt at a specified effort tier), Interview (adaptive question-and-answer to fill in or deepen sections), CheckCompleteness (score an existing ISA against the tier completeness gate and report gaps), Reconcile (deterministic merge of an ephemeral feature-file excerpt back into the master ISA, keyed on stable ISC IDs), Seed (bootstrap a draft project ISA from an existing repository's README, code structure, and recent commits). Examples directory contains canonical-isa.md (the showpiece reference, fully populated across all twelve sections), e1-minimal.md (90-second task — Goal + Criteria only), e3-project.md

Structured multi-angle exploration that runs 2-8 sequential passes through the same problem, each from a systematically different scientific lens, to surface requirements and edge cases invisible from any single angle. Grounded in 20 established techniques across cognitive science (Hermeneutic Circle, Triangulation), AI/ML (Self-Consistency, Ensemble Methods), requirements engineering (Viewpoint-Oriented RE), and design thinking (Six Thinking Hats, Causal Layered Analysis). Each pass outputs new ISC criteria; passes stop when yields repeat. Best used in the OBSERVE phase at Extended+ effort — the default question should be why NOT to use it, not why to use it. A 4-lens pass routinely discovers 30-50% more criteria than direct analysis. Single workflow: Workflows/Explore.md (supports Fast mode with 2 lenses for quick depth). Reference files: ScientificFoundation.md (research grounding for all 20 techniques), TheLenses.md (full definitions for all 8 lenses). BPE-fragile — quarterly test recommended. NOT FOR sco

Manage the PAI Knowledge Archive — a curated, typed graph of notes across four entity domains: People, Companies, Ideas, and Research. Operations: search (3-pass: lexical + frontmatter + wikilink), add (creates note with mandatory typed cross-links), harvest (KnowledgeHarvester pulls from PAI sources), develop (surfaces seedling notes for enrichment), ingest (fetch URL or file, create primary note, ripple updates to related notes), contradictions (find conflicting claims via tag-overlap pairs), graph (stats or 2-hop traversal via KnowledgeGraph.ts), retrieve (BM25-lite compressed context via MemoryRetriever.ts), mine (SessionHarvester extracts memory candidates from recent conversations). Every note ships with typed related: frontmatter links (8 relationship types: supports, contradicts, extends, part-of, instance-of, caused-by, preceded-by, related). USE WHEN knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, ingest, contrad

Programmatic video creation with React via Remotion — compositions, animations, motion graphics, rendered to MP4. USE WHEN video, animation, motion graphics, video rendering, React video, intro video, YouTube video, TikTok video, video production, render video, content to animation, animate content, video overlay.

Intakes existing content from external sources, classifies each chunk against the PAI destination taxonomy, and commits approved chunks with provenance. Sources: .md/.markdown/.txt, stdin, PAI TELOS/MEMORY/KNOWLEDGE dirs, CLAUDE.md/.cursorrules/OpenAI Custom Instructions, Obsidian/Notion/Apple Notes exports, journal dumps. MigrateScan.ts chunks and classifies, producing a routing table with per-target counts and confidence %. MigrateApprove.ts approval loop: --approve-all, --approve-target, --review, --dry-run. UNCLEAR never bulk-approved. Phase 6 delivers summary and /interview recommendation for sparse areas. Confidence: ≥70% auto-approve; 40-70% confirm; <40% walk-through. Destinations: TELOS (MISSION/GOALS/PROBLEMS/STRATEGIES/CHALLENGES/BELIEFS/WISDOM/MODELS/FRAMES/NARRATIVES/SPARKS), IDEAL_STATE (per-dimension explicit call), preferences (BOOKS/AUTHORS/MOVIES/BANDS/RESTAURANTS/FOOD_PREFERENCES/LEARNING/MEETUPS/CIVIC), Identity (PRINCIPAL_IDENTITY.md — always prompts), Knowledge (MEMORY/KNOWLEDGE/{Ideas,P