synthesis-skills

Post-implementation verification protocol that catches incomplete work, hidden shortcuts, and gaps between 'tests pass' and 'production works.' Systematically traces data chains, detects placeholders, audits test honesty, and verifies environment parity. Use when asked to: verify implementation, check completeness, implementation review, is this done, built properly, no shortcuts, verify work, completion check, integrity check, self-review, pre-PR check, ship check.

Lightweight project management system designed for human-agent collaboration, optimized for context preservation across sessions. Use when asked to: project management, project setup, project tracking, synthesis project, manage project, set up project, project structure, session protocol.

Validate, convert, and author content for Google's Open Knowledge Format (OKF v0.1) — the markdown-plus-YAML-frontmatter knowledge-bundle spec announced 2026-06-12. Includes a conformance validator (the checker Google's own OKF repo ships none of), a converter that backfills OKF frontmatter onto an existing markdown corpus idempotently, and the proven repo-by-repo conversion procedure. Use when adopting OKF for an "LLM wiki" style knowledge base, auditing conformance, or converting a corpus of markdown notes/docs into a conformant, agent-readable bundle.

Discipline for catching the lazy-shortcut antipattern in AI-assistant output. Makes the costume vocabulary explicit so agents recognize when their drafts have slid into deferral, dismissal, or false consultation. Includes the constraint-first protocol, sub-agent dispatch and acceptance hygiene, and a pre-response self-check. Use when asked to: avoid shortcuts, audit for laziness, check for deferral, enforce best solution, no shortcuts, anti-shortcut, constraint-first, sub-agent hygiene, costume vocabulary.

Cross-provider model-tier convention for agentic work: three role labels (judgment, routine, bulk — formerly frontier, efficient, light) resolved to current model IDs per provider in tiers.yaml, so skills, project docs, and memory never hardcode model names. Use when asked about: model tiers, which model, model selection, judgment model, routine model, bulk model, frontier model, efficient model, switch models, model equivalents across providers, update model table.

Fetch AI-generated meeting notes and full transcripts (e.g., Google Meet + Gemini) from the user's Gmail/Drive into local markdown files. Tool-agnostic: works with any Gmail + Drive MCP (Anthropic hosted connectors, self-hosted workspace-mcp, or others). Replaces the manual email → Google Doc → export-markdown → Downloads → move workflow. Use when asked to: fetch meeting transcript, pull standup, grab meeting notes, sync meetings, download transcript, get Gemini notes, import meeting.

Reconcile pending, missed, and incomplete commitments after any gap in the daily-ritual cadence (travel, family visits, crunch weeks). Sweeps daily plans, transcripts, and project context over an arbitrary window; classifies every surfaced item (including expired-for-learning); produces a dated catch-up ledger document; routes survivors without flooding the daily plan. Use when asked to: catch up on missed tasks, sweep pending items, catch-up ledger, reconcile backlog, what did I miss, post-vacation catch-up, falling behind recovery.

Day-start and day-end checklists for synthesis engineering projects. Execute dependency-ordered rituals for context optimization, Slack sync, catch-up reads, PR reviews, day planning, and communications. Use when asked about: daily ritual, morning routine, day start, day end, daily checklist, morning checklist, end of day checklist, daily workflow.

Autonomous-execution mode for explicitly delegated work. A thin composition layer that sequences the synthesis stack — thinking framework for decisions, plan file + context lifecycle + checkpoint for compaction survival, anti-shortcuts for solution quality, implementation integrity for verification — so one delegation phrase replaces a retyped block of standing instructions. Activate ONLY on explicit whole-task delegation: take care of this for me, autopilot this, handle this end to end, run with it with minimal check-ins, complete all phases autonomously, I trust you to finish this without me. Do NOT activate on vague keyword matches, on 'go ahead' approval of a single step, on discussion about autonomy, or on any ambiguous phrasing — users supervise some work by choice, and under-firing costs only a few extra check-ins while over-firing removes supervision the user wanted.

Multi-Mac configuration sync via iCloud with bidirectional config file sync, git repository sync, machine inventory, and one-time action system. Use when asked to: mac sync, sync config, sync repos, sync with GitHub, push config to iCloud, pull config from iCloud, run mac-sync, repo status.

Workspace git-sync guard: detects uncommitted/unpushed repos, reports through confidentiality-safe channels (generic audio/banner + detailed report files + synthesis-console tile), and auto-heals private context repos at workflow events via checkpoint_sync.py. Works with any AI coding tool (Claude Code, Codex, Cursor, etc.) or standalone. Use when asked to: repo guard, check repos, session end check, sync check, repo status, workspace status, checkpoint sync, auto-commit context repos.

Three-tier context architecture for managing AI working memory across long-running projects. Use when asked to: manage context, project context, session management, context lifecycle, working memory, archival, archive sessions, context maintenance, garbage collection for context, tiered context.

Manifest-driven email inbox cleanup across three tool stacks: iCloud / generic IMAP via Python + YAML rules; Microsoft 365 + outlook.com via Mail.app AppleScript; Gmail via workspace-mcp Gmail API and server-side filters. Engine is public; per-user rules live privately at ~/.synthesis/inbox-cleanup/. Ships with prompt-injection defenses (sanitization module + adversarial test fixtures) for any LLM-augmented path. Use when asked to: clean up inbox, sweep email, categorize senders, build email rules, archive promotions, set up Gmail filters, build email cleanup automation.

Refresh and revitalize older articles with improved clarity, presentation, and completeness while preserving the author's voice, argument, and period-appropriate context. Standard editorial practice for keeping a published archive polished and accessible. Use when asked to: refresh article, revitalize article, update older article, polish published post, enhance older content.

Three-phase workflow for creating high-quality thought leadership articles: research and validation, strategic writing, and pre-publication critical review. Includes anonymization protocol, credibility assessment, substance density checks, and engagement optimization. Use when asked to: write article, thought leadership, blog post, article workflow, write blog, draft article, create thought piece, write opinion piece, leadership article.

Find authoritative hyperlinks for people, organizations, and entities mentioned in content; recover dead URLs in archives via Wayback / Wikipedia / strip prioritization. Use when asked to: find links, hyperlink, research links, find URLs, gather references, look up websites for people or organizations, recover dead links, fix link rot, find archived versions.

Mid-session refresh and drift-recovery protocol. Re-syncs the agent's awareness of current date, project state, and recent commit history when context may have drifted from disk. Use when asked to: checkpoint, re-sync, refresh context, mid-session refresh, recover from compaction, re-read project state, verify dates, drift check, where are we, what was last done, am I caught up. Invoke on any suspicion of context drift, after long conversation pauses, or before generating time-interval claims.

Content framing methodology for synthesis engineering articles. Covers topic selection, sophistication standards, engagement patterns, quality gates, and operational rules for publishing technical thought leadership. Use when writing synthesis engineering content, framing technical articles, checking content quality gates, or publishing thought leadership.

The most comprehensive open-source slop detection system available. Catches AI-generation patterns by model family (Claude, GPT, Gemini, Llama, Grok, DeepSeek, Mistral, Qwen), substance and depth failures (beautiful word salad), and the full v3.1.0 catalog refreshed. Includes causal-layer attribution, combined-signal fingerprints, two-axis calibration, ESL safe-harbor, and zone-conditional detection (artifact mode vs full-response mode). Spans the entire LLM era through the compounding-archive principle. Use for content quality, slop detection, AI content auditing, editorial review, content improvement, and publishing standards.

Produce text without watermarking patterns, invisible characters, or statistical fingerprints that identify text as AI-generated. Use when generating clean text, avoiding watermarks, addressing AI detection concerns, or producing text generation output that should be free of hidden markers.

Strategically promote and distribute content across social media platforms to build thought leadership, spark discussion, and create professional connections. Provides platform-specific guidelines, engagement strategies, cross-platform coordination, and quick-start templates for blog promotion and event/topic posts. Use when asked to: promote content, content distribution, social media strategy, share article, social media post, write tweet, LinkedIn post, Instagram post, promote blog, blog promotion, post about event, content marketing, distribute post, promote article, social media promotion.

Systematic fact-checking for articles, blog posts, news content, and AI-synthesized material. v2.0 adds nine new protocol sections covering nested attribution, paraphrase drift, composite quotes, position-shifting, source-translation drift, URL rot vs hallucination, AI-generated synthetic sources, citation laundering chains, and tool-specific hallucination patterns by LLM family. Use when asked to: fact-check, verify claims, verify sources, check accuracy, citation verification, review factual accuracy, validate references, audit AI-summarized content.

Positive writing principles synthesized from the centuries-old writing-craft tradition. Covers sentence-level craft, paragraph and pacing, voice and honesty, structure (openings and closings), process and discipline, and revision. Intended as an operating guide for AI agents working on a writer's behalf — not teaching material for human writers, not a substitute for the canonical books on the recommended-reading list. Use alongside synthesis-content-quality (AI-pattern detection) and synthesis-writing-pitfalls (human-source pattern detection).

Universal bad-writing patterns produced by human authors and editors, independent of AI. Covers cringe (humble-bragging, defensive disclaimers, third-person self-reference in personal writing, pre-emptive originality defense, apologizing-while-bragging), throat-clearing, caveat overload, reader-relationship missteps, sentence-level weakness, cliché reliance, and stilted formality. Use when reviewing or editing prose for craft failures, doing archive scans, self-editing drafts, or training writers and editors. Apply alongside synthesis-content-quality (AI-specific patterns) and synthesis-writing-craft (positive principles).

Deterministic pre-commit policy for the synthesis-engineering workflow. Auto-classifies each repo by its push remotes (personal vs strict), applies a tiered pattern set: Tier 0 credentials always; Tier 1 financial / HR / confidentiality / client names only in strict repos. YAML-driven policy lives in ~/.synthesis/git-hook-config.yaml. Use when asked to: install git hooks, configure pre-commit policy, prevent credential leaks, prevent confidential-name leaks in public repos, set up the synthesis-engineering enforcement layer.

Agent-native skill installer and manager for the synthesis skills ecosystem. Handles installation, drift detection, synthesis merge for conflicts, provenance tracking, and cross-repo coordination. Use when asked to: install skills, update skills, check skill drift, manage skills, skill status, skill inventory, sync skills.

Pre-writing reader briefing methodology for public articles. A required precondition for any article that draws on internal source material (lessons, project context, codebases) and is published to an external audience. Catches insider context collapse before it becomes a draft. Use when asked to: write article, plan article, brief audience, audience analysis, reader briefing, pre-writing, before drafting, who is this for.

Slack channel sync protocol for AI-assisted workflows. Reads channels and threads via Slack MCP, saves to local transcript files in workspace-scoped repos, and updates person-scoped daily action plans. Handles mid-day re-syncs with thread staleness detection. Use when asked to: slack sync, sync from slack, check slack, read channels, sync messages, sync transcripts, what's new on slack.

Condense messages to 5 sentences or less using the High-Five Habit framework. Produces concise, effective business communications across email, Slack, text, and social media. Use when asked to: condense message, shorten email, brief message, concise writing, email template, make shorter, tighten email, reduce message length, write concise message.

Delta review methodology for pull requests in synthesis-coded projects, covering regression risk assessment, root cause analysis, and integration with the adopt-and-adapt workflow. Use when asked to: PR review, pull request, code review, review PR, delta review, review pull request, check PR, evaluate PR.

Generate a structured writing voice profile from sample texts and diagnostic questions. Outputs an agent-instruction voice section that other skills automatically consume. Use when asked to: create voice profile, analyze writing style, extract voice, profile my writing, build voice section, writing DNA, style analysis.

Systematic 10-dimension quality scan of code diffs, producing scored PASS/WARNING/FAIL verdicts per dimension with a machine-readable overall result. Includes PR review mode for cross-referencing findings against existing reviewer comments. Use when asked to: code audit, audit my changes, quality check, review the diff, check this code, audit my code, scan for issues, code quality scan, diff review.

The adopt-and-adapt integration pattern for multi-contributor synthesis-coded projects. Covers the lead synthesist role, quality gates, cherry-pick safety, and graduated integration intensity. Use when asked to: synthesis coding, multi-contributor, integration, cherry-pick, adopt and adapt, lead synthesist, integrate contributions, merge contributor work.

Structured approach to code generation, implementing features, and writing code. Use when asked to generate code, implement a feature, write code, or tackle a coding task. Analyzes the task, generates multiple approaches with trade-offs, selects the optimal solution, and implements it.

Enterprise-scale codebase audit methodology with tiered review system (Essential through Mission-Critical). Use when asked to: codebase review, code audit, code review, review codebase, architecture review, security audit, full code review, enterprise review, codebase health check.

Configure an LLM as a creative writing coach and editor. Use for creative writing, writer setup, configure writer, creative assistant, content creation coaching, storytelling assistance, and writing improvement.

Guide for setting up and configuring LLM projects across platforms. Use when setting up a Claude Project, creating a ChatGPT GPT, configuring a Gemini Gem, setting up an AI assistant with custom instructions and knowledge, or configuring any LLM platform with AI Knowledge content.

Pre-merge quality gate framework with six orthogonal dimensions: branch hygiene, clean tree, tests and types, code audit, temporary considerations, and commit history. Produces a mechanical go/no-go verdict. Use when asked to: preflight, pre-merge check, ready to merge, can I ship this, branch ready, quality gate, merge readiness, pre-PR check.

Combine multiple LLM responses into a single unified document. Use when asked to combine responses, merge outputs, synthesize responses, unify documents, or consolidate multiple AI-generated answers into one comprehensive result.

PR queue prioritization methodology with weighted scoring across review gap, CI status, age, size, and labels. Includes author-response detection, queue classification, and prior-review gate for deciding full audit vs. delta-only vs. skip. Use when asked to: triage PRs, which PR should I review, review queue, prioritize reviews, PR backlog, review priority, what needs review, PR triage, review workload.