「proof」の検索結果

Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASK_ID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.

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Turn client wins into formatted case studies for proposals, social proof, and sales conversations. Use when someone needs to document results, build credibility, or create reusable proof assets.

日本語の概要は準備中です。原文の説明を表示しています。

Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.

日本語の概要は準備中です。原文の説明を表示しています。

Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.

日本語の概要は準備中です。原文の説明を表示しています。

Turn real customer reviews, quotes, and case-study results into polished social-proof videos built in HyperFrames -- single-testimonial spotlights, review-wall montages, and stat-driven proof reels with captions and voiceover, cut for vertical, square, and wide. The highest-converting content most businesses never make.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when the user asks to "line edit", "edit my prose", "polish this chapter", "tighten the prose", "improve the sentences", "copyedit", "proofread", "proof pass", "check grammar and punctuation", "dialogue punctuation", "make the voices distinct", "everyone sounds the same", "read it aloud", "read-aloud pass", "text to speech", or wants a sentence-level quality pass on drafted chapters that preserves the author's voice. NOT for creating the style sheet, recording character voices, or checking voice consistency (use voice-style).

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Comprehensive PET selection guide covering differential privacy, homomorphic encryption, secure multi-party computation, federated learning, zero-knowledge proofs, and trusted execution environments. Includes use-case matching matrix, performance comparison, and GDPR alignment assessment for each technology.

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Generate systematic refinement steps from high-level specifications to concrete implementations in Isabelle/HOL or Coq, preserving correctness obligations at each step. Use when working with formal verification, program refinement, proof development, or when translating abstract specifications into executable code while maintaining formal guarantees. Supports data refinement (abstract types → concrete structures), algorithmic refinement (specifications → algorithms), and stepwise refinement with proof obligations.

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Uses abstract interpretation to automatically infer loop invariants, function preconditions, and postconditions for formal verification. Generates invariants that capture program behavior and support correctness proofs in Dafny, Isabelle, Coq, and other verification systems. Use when adding formal specifications to code, generating verification conditions, inferring contracts for functions, or discovering loop invariants for proofs.

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Research and collect social proof — testimonials, case studies, user reviews, social mentions, and community endorsements across platforms. Useful for marketing teams building trust content, landing pages, and sales collateral from authentic customer voices.

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How to use the Boundless CLI — the primary interface for the Boundless ZK proof marketplace. Covers requestor, prover, and rewards commands, config, env vars, and the monorepo structure. Use when working with the boundless CLI, submitting proofs, managing provers, staking rewards, or navigating the codebase.

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Start and interact with the Boundless localnet (docker compose-based local development network). Covers dev mode (fake proofs, broker included) and full proving mode, submitting requests, and debugging order flow. Use when the user wants to start localnet, run the local network, test proof requests locally, or debug broker/order-stream issues.

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Systematically harvest short testimonials from customers via NPS, milestones, post-purchase, and email during PRD v1.0 Market Adoption. Triggers on requests to collect testimonials, set up social proof harvest, gather customer quotes, or when user asks "how do we get testimonials?", "social proof harvest", "NPS responses", "testimonial wall", "customer quotes", "post-purchase survey", "milestone follow-up". Outputs CFD-TST-* testimonial entries and GTM-TST-* placement assets.

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Build the deterministic evidence ledger (artifact_manifest.json + claims.json) that every other Anti-Autoresearch auditor reads. One pass inventories artifacts, derives the observability level (L0 PDF-only / L1 +LaTeX / L2 +repo+results) by fixed rule, and extracts span-anchored, hashed, checkable claims (numbers, comparisons, scope, method, baselines, citations, captions, table cells) into claims.json. An OPTIONAL additive cross-model pass ADDS span-anchored semantic claims — method, theorem statements with their assumptions, definitions, proof/derivation steps and equations, scope, baselines, conclusions, the motivation span, and reproducibility-artifact references (the proof, derivation, and structure anchors the family B/D/G auditors need) — it never invents a number, emits a finding, or computes a verdict. Run FIRST, before any audit skill. Triggers: "build the ledger", "extract claims", "prep for integrity audit", "evidence ledger", "建证据账本".

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Use when building a feature, refactoring, fixing a complex bug, changing architecture, or starting any non-trivial coding task. 12-stage verified dev workflow from research to deploy.

日本語の概要は準備中です。原文の説明を表示しています。

Present attributable testimonials and proof.

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Comprehensive blog writing skill that handles technical blog posts, personal voice writing, brain dump transformation, and category-aware AEO-optimized content. Use when: (1) writing, editing, or proofreading a blog article or post, (2) transforming unstructured brain dumps into polished posts, (3) writing in specific personal voices (Jarad, Nick Nisi), (4) creating category-aware technology/company/product posts, (5) building tutorials, deep dives, postmortems, benchmarks, or architecture posts, (6) writing engineering blogs, dev blogs, programming blogs, coding tutorials, or documentation posts. Triggers: blog post, blog writing, technical blog, dev tutorial, brain dump, article, content writing, developer article, engineering blog, programming blog, coding tutorial, documentation post, technical writing, blog editing, proofreading, developer content

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Provides domain knowledge and guidance for the Flare Data Connector (FDC)—attestation types, request flow, Merkle proofs, verifier/DA Layer, and smart contract integration. Use when working with FDC, cross-chain attestations, EVMTransaction, Web2Json, Payment, AddressValidity, proof-of-reserves, weather insurance, or Flare Developer Hub FDC guides and starter repos.

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CoSProver framework for translating informal proofs to Lean4 via intermediate formal proof states.

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Use after an Anabasis run, comparison, or system change and before claiming improvement. Attributes movement to one owner, reports identities and censored denominators, separates deterministic proof from model judgement, keeps measurement validity apart from observed exploitation, and states what remains unrun or provisional.

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Analyze the documents for spelling, capitalization, punctuation, word break, or grammar errors. Use when the user wants to "proofread" or "spellcheck" a document.

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Use when C or C++ code needs memory-safety or undefined-behavior guarantees proved with CBMC, or ACSL contracts checked with Frama-C Eva or WP. Not for choosing the proof policy: use proof-driven.

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Use when Rust code, especially unsafe or panic-critical paths, needs a Kani, Verus, or Creusot harness written, run, and its failure read. Not for choosing the proof policy: use proof-driven.

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Expert copy editor for Quarto (.qmd) files. Checks grammar, spelling, punctuation, and academic writing quality. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to proofread, check grammar, fix typos, or review prose in a .qmd document. For APSA style rules (numbers, citations, capitalization, abbreviations, neutral language), use the apsa-style skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

日本語の概要は準備中です。原文の説明を表示しています。