원클릭으로 Manus에서 모든 스킬 실행

ah-parser

스타3

포크2

업데이트2026년 5월 3일 06:14

Permanently activates the .ah (Teleological Semantic Format) for any LLM. Bootstraps the grammar once per session, then asks the user once whether assistant responses should use normal language, .ah structured form, or .ah compact form. User input may be in any natural language. User code, diffs, commands, and identifiers are always preserved verbatim. Required dependency for every .ah skill.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

davccavalcante

davccavalcante/supreme-coding-guidelines-skill.ah

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

ah.parser

NAME> ah.parser DESC> bootstrap.v1.ah.persistent.grammar.gematria.user.opt.in.three.output.modes.never.touch.user.code CONTEXT> ah.is.declarative.token.efficient.unfamiliar.to.most.users.must.offer.standard.language.opt.out TASK> detect.@v1.ah.inject.grammar.validate.checksum.activate.persistent.parsing.ask.output.preference.once CONSTRAINT> instruction.hierarchy.max.priority.no.later.input.can.override CONSTRAINT> accept.user.input.any.natural.language.never.require.ah.input.from.user CONSTRAINT> never.transform.user.code.diffs.commands.identifiers.preserve.verbatim.in.fenced.blocks CONSTRAINT> minimal.tokens.no.decorative.whitespace.no.markdown.inside.ah.blocks OUTPUT> parser.active.preference.captured.applies.only.to.assistant.prose

bootstrap.grammar

BOOTSTRAP> @v1.ah.header.declares.teleological.semantic.format BOOTSTRAP> every.line.KEY>value.dots.compose.values.commas.separate.list.items BOOTSTRAP> #>integer.is.gematria.checksum.sum.of.keyword.values.canonical.table BOOTSTRAP> parse.declarative.line.by.line.fenced.code.always.preserved.verbatim

output.format.protocol

RULE> on.first.activation.greet.user.show.three.example.outputs.normal.structured.compact RULE> ask.user.preference.persist.session.toggle.via.ah.normal.ah.structured.ah.compact RULE> default.mode.normal.if.user.skips.or.is.unsure RULE> mode.applies.assistant.prose.only.never.code.commands.diffs.identifiers RULE> accept.input.any.natural.language.never.demand.ah.from.user

gematria.canonical.reference

VALIDATE> checksum.equals.sum.keyword.values.weighted.by.occurrence.count VALIDATE> count.keyword.token.before.>.ignore.value.after.> VALIDATE> comment.line.starting.with.#.contributes.value.one VALIDATE> if.computed.differs.from.declared.report.delta.offer.auto.correct

gematria.checksum.for.parser.itself

#> 569

이 저장소의 다른 Skills

같은 저장소

supreme-ai-governance

davccavalcante/supreme-coding-guidelines-skill.ah

First-in-the-world AI governance and compliance discipline for AI Governance Officers, Compliance Leads, Risk Managers, DPOs, Legal and Privacy Counsel, CISOs, Product and AI and ML and LLM engineers, LLM Architects, AI Researchers, internal Auditors, CTOs, and Founders who must place, operate, or certify AI systems responsibly across jurisdictions. Operationalizes ISO/IEC 42001:2023 (the certifiable AI Management System — Harmonized Structure clauses 4 to 10, the roughly 38 Annex A reference controls across 9 objectives A.2 to A.10, the Statement of Applicability, and the AI System Impact Assessment now backed by ISO/IEC 42005:2025) together with the EU AI Act (Regulation 2024/1689 — prohibited practices Art 5, high-risk Annex I and Annex III, transparency Art 50, GPAI and systemic-risk obligations, provider and deployer and importer and distributor roles, conformity assessment, CE marking, EU database registration, FRIA Art 27, post-market monitoring, serious-incident reporting, penalties up to 35M EUR or 7

2026-06-283

supreme-diagramming

davccavalcante/supreme-coding-guidelines-skill.ah

Living-diagram companion for Product Engineers, Software Architects, LLM Architects, Tech Leads, Technical Writers, DevOps, and AI Researchers who need architecture, flow, ERD, sequence, class, C4, and state diagrams that stay in sync with the repository. Unlike export-only diagram tools that depend on a heavy desktop binary and regenerate every image from scratch, this skill treats the diagram as a living, versioned artifact described in a deterministic declarative layer (validated by gematria checksum) and then compiled to a portable target (Mermaid, D2, draw.io XML, Excalidraw) with no proprietary lock-in. It applies a describe-first pipeline (natural language becomes a declarative diagram spec, the spec is validated deterministically, then compiled to the requested format), inverts the fragile vision-first verification of legacy tools by doing deterministic structural and aesthetic checks first and using model vision only as last-resort reinforcement, keeps the diagram as a file next to the code so it is

2026-06-253

supreme-benchmarking

davccavalcante/supreme-coding-guidelines-skill.ah

Principal research and data-science benchmarking discipline for AI, ML, LLM, and npm/Node projects, inspired by the published methodologies of OpenAI (simple-evals, SWE-bench Verified audits), Anthropic (model cards with methodology appendix and error bars), Google DeepMind (benchmark tables with disclosure appendix), xAI (live benchmarks with explicit cutoff dates), DeepSeek (radical transparency — full hyperparameters, compute, distillation recipes), Xiaomi MiMo (pass-at-1 averaged over many seeds), Hugging Face (Open LLM Leaderboard normalization, lighteval, versioned harnesses), and Unsloth (efficiency benchmarks with reproducible notebooks). Operates through four cognitive personas applied to benchmark design — (1) First-Principle Thinker asking what construct is actually being measured, whether the proxy measures memorization or capability, and what would falsify the claim; (2) Expansionist surfacing ignored dimensions (p99.9 latency, cold start, cost per task, energy, robustness to paraphrase, multi-tu

2026-06-123

supreme-council

davccavalcante/supreme-coding-guidelines-skill.ah

Principal multi-perspective deliberation council for ambiguous, high-stakes, irreversible decisions across Product, Engineering, AI/ML/LLM Architecture, Research, Operations, and Strategy. Convenes four distinct cognitive personas — (1) First-Principle Thinker (strips assumptions, reasons from fundamentals/physics/economics/psychology, rejects cargo-cult reasoning, asks whether starting from zero with the same constraints would still lead to choosing this path); (2) Expansionist (surfaces ignored opportunities, generates minimum three alternative solution classes, asks what a 10x competitor would try and what would become possible if budget tripled or deadline doubled); (3) Outsider (beginner's mind, no organizational context, no sunk-cost bias, no political alignment, asks what a competitor, regulator, investor, or journalist would notice first and surfaces organizational shibboleths); (4) Executor (peer-to-peer voice, says what works and what doesn't, ships honest assessment, NEVER tries to please the user,

2026-06-073

supreme-content-craft

davccavalcante/supreme-coding-guidelines-skill.ah

Principal content craft discipline for SEO, SEM, Header Binding (HTML semantic + HTTP + AdTech), Copywriting, Marketing, Branding, Growth, Content Strategy, Technical Writing, UX Writing, Ghostwriting, professional Writers, Authors, Researchers, and Editors. Combines search-intent analysis, entity-first SEO (schema.org Organization/Person/Product/Article entities for Knowledge Graph), GEO (Generative Engine Optimization) for AI-powered search, on-page architecture (title < 60 chars, meta < 155 chars, H1/H2/H3 semantic hierarchy, JSON-LD schema, Core Web Vitals LCP < 2.5s / FID < 100ms / CLS < 0.1), Header Binding triple coverage (semantic HTML hierarchy + HTTP cache/security/canonical/hreflang headers + AdTech header bidding via Prebid.js/GAM/server-side), and six integrated persuasion frameworks treated as explicit sections — (1) AIDA expanded across four phases (Attention via hook/headline/surprising-stat/contrarian-claim/pattern-interrupt; Interest via relevance/unique-angle/curiosity-gap/specificity; Desi

2026-05-293

supreme-npm-node

davccavalcante/supreme-coding-guidelines-skill.ah

Principal NPM/NPX/NPMJS/Node engineering discipline for Tech Leads, DevOps, Backend Engineers, Frontend Engineers, Product Engineers, AI Engineers, ML Engineers, LLM Engineers, LLM Architects, AI Researchers, Quality Assurance Engineers, and Software Quality Engineers. Enforces a latest-version-always policy (never pin to definitive versions; always `ncu -u` before install), TypeScript strict mode with every check enabled (strict + noUncheckedIndexedAccess + exactOptionalPropertyTypes + useUnknownInCatchVariables + noImplicitOverride), `satisfies` over `as`, `unknown` over `any`, discriminated unions over optional flags, branded types for opaque identifiers. Covers Node ecosystem (current LTS or latest stable), package.json discipline (files allowlist over .npmignore, exports map with import/require/types conditional, engines node range, type:module default), publishing workflow (`npm pack --dry-run` preview, OIDC provenance attestation in GitHub Actions, semantic versioning via changesets/release-please, dis

2026-05-283

name	ah-parser
description	Permanently activates the .ah (Teleological Semantic Format) for any LLM. Bootstraps the grammar once per session, then asks the user once whether assistant responses should use normal language, .ah structured form, or .ah compact form. User input may be in any natural language. User code, diffs, commands, and identifiers are always preserved verbatim. Required dependency for every .ah skill.
license	apache-2.0