Strip AI writing patterns from prose across five registers — casual, professional, academic, technical, and narrative. Applies 200+ pattern rules to eliminate predictable LLM tells. Triggers on clean up writing, remove AI slop, edit prose, make this sound less AI.
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Eliminate predictable AI writing patterns. Produce clear, specific, human-sounding prose across any register.
Infer the register from context before applying rules. Different registers tolerate different patterns.
| Signal | Register |
|---|---|
| Citations, methodology, "we hypothesize" | academic |
| API docs, READMEs, changelogs, error messages | technical |
| Fiction, essays, memoir, creative nonfiction | narrative |
| Blog posts, social media, emails | casual |
| Reports, proposals, business comms | professional |
If the user specifies a register, use it. See references/registers.md for per-register acceptable vs. flagged patterns.
Apply these rules, adjusted for register:
Cut filler phrases and AI vocabulary. Remove throat-clearing openers, chatbot artifacts, significance inflation, and words that appear 100-1,000x more in LLM output than human text. See references/phrases.md.
Break formulaic structures. Avoid binary contrasts, dramatic fragmentation, format slop, synonym cycling, rule-of-three overuse, and generic conclusions. See references/structures.md.
Use simple constructions. Prefer "is" over "serves as." Prefer "has" over "boasts." Prefer "use" over "leverage." Active voice. Positive form.
Be specific. Replace vague claims with dates, names, numbers, sources. "Significant improvement" becomes "latency dropped from 340ms to 90ms."
Vary rhythm. Mix sentence lengths. Two items in a list beat three. End paragraphs differently from each other.
Trust readers. State facts. Skip softening, justification, hand-holding. If a metaphor needs explaining, rewrite the metaphor.
Have a voice. React to facts, don't just report them. Acknowledge complexity. Let personality through.
See references/positive.md for what good writing does (not just what to avoid).
Rate 1-10 on each dimension, adjusted for register:
| Dimension | Question |
|---|---|
| Directness | Statements or announcements? |
| Rhythm | Varied or metronomic? |
| Trust | Respects reader intelligence? |
| Authenticity | Sounds human, not generated? |
| Density | Anything cuttable? |
| Specificity | Claims backed by evidence? |
Below 42/60: revise.
Register adjustments (see references/registers.md):
academic: Do not penalize precise hedging or longer qualified sentencestechnical: Consistent structure in reference docs is not a rhythm flawnarrative: Indirection and dramatic rhythm variation are valid techniquesBefore delivering prose:
| File | Purpose |
|---|---|
| phrases.md | Words and phrases to cut or replace |
| structures.md | Structural patterns to avoid |
| positive.md | What good writing does |
| registers.md | Per-register rules and tolerances |
| examples.md | Before/after transformations (all registers) |
MIT
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Search academic papers, build literature reviews, and synthesize research findings — combines Exa search (publication category, domain and date filters) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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This skill should be used when creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
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Academic research skill for Biblical Hebrew, Semitic linguistics, cuneiform studies, and comparative Ancient Near Eastern research. Provides Sefaria API for Hebrew Bible, CDLI/ORACC for cuneiform databases, and web discovery via Omnisearch, Exa, Firecrawl, and Obscura for finding scholarly sources across JSTOR, Perseus, Persée, Google Scholar, and academia.edu. Triggers on Hebrew quotes, cuneiform, Sefaria, ANE research, Minoan, search for scholarship, find papers, literature review, scholarly search, academic search, Genesis/Tehom, Ugaritic, Talmudic sources, extract from PDF, OCR academic.
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Build comprehensive ARCHITECTURE.md files following matklad's canonical guidelines — bird's-eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries. Triggers on document the architecture, create ARCHITECTURE.md, map this codebase, architectural overview.
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Generate physically-based atmospheric scattering shaders — sky domes, planetary atmospheres, LUT-optimized pipelines, depth-aware post-processing. Four modes — sky-dome, atmosphere-post, planet, lut. Triggers on atmospheric scattering, sky shader, sunset rendering, planet atmosphere, Rayleigh scattering, Mie scattering, volumetric sky, sky dome, atmosphere post-processing, aerial perspective, transmittance LUT, sky rendering, realistic sky, planetary rendering.
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