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cccskills

「perma」の検索結果

103 件 ・ 関連度順

概要と使いどころ

Add GitHub permalinks with fixed SHA/commit references to research documentation containing code snippets. Use when writing technical docs with code examples, creating investigation/research docs that reference source files, user asks to "add permalinks" or "add GitHub links", documenting code research findings with file:line references, or creating audit trails needing permanent code references. Triggers on "add github links", "add permalinks", "link to source", "make code references permanent".

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。

t4ku/agent-skills52026年10月7日 更新

Analyze DEX liquidity pools for TVL, volume, fees, impermanent loss, and LP profitability. Use when analyzing liquidity pools, calculating impermanent loss, or comparing DEX pools. Trigger with phrases like "analyze liquidity pool", "calculate impermanent loss", "LP returns", "pool TVL", "DEX pool metrics", or "compare pools".

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。

jeremylongshore/tons-of-skills-marketplace2,8322026年10月13日 更新

Design a lesson that embeds PERMA wellbeing elements alongside academic learning objectives. Use when planning lessons that intentionally support both content mastery and student flourishing.

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。

GarethManning/education-agent-skills8502026年8月29日 更新

Design a lesson that embeds PERMA wellbeing elements alongside academic learning objectives. Use when planning lessons that intentionally support both content mastery and student flourishing.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

positive-psychology

無料日本語概要

セリグマンのポジティブ心理学:PERMAモデル、強み(VIA)、感謝のエクササイズ、フロー理論、レジリエンス要因。

ellmos-ai/skills82026年10月12日 更新

promote

無料

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.

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。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

paperkit

無料

Add drawings, shapes, and a consistent markup experience using PaperKit. Use when integrating PaperMarkupViewController for markup editing, adding shape recognition, working with PaperMarkup data models, embedding markup tools in document editors, or building annotation features that need the system-standard markup toolbar. New in iOS 26.

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。

dpearson2699/swift-ios-skills1,1922026年8月1日 更新

Expert blueprint for roguelikes including procedural generation (Walker method, BSP rooms), permadeath with meta-progression (unlock persistence), run state vs meta state separation, seeded RNG (shareable runs), loot/relic systems (hook-based modifiers), and difficulty scaling (floor-based progression). Use for dungeon crawlers, action roguelikes, or roguelites. Trigger keywords: roguelike, procedural_generation, permadeath, meta_progression, seeded_RNG, relic_system, run_state.

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。

thedivergentai/Game-Design-Agentic-Skills8452026年10月13日 更新

Impermanent loss calculation, modeling, and breakeven analysis for AMM liquidity provision across pool types

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。

agiprolabs/claude-trading-skills4112026年9月3日 更新

tax-invoice-credit-context

無料日本語概要

Background context for invoice-system input tax credit rules (仕入税額控除) in the shinkoku tax filing plugin. Contains eligibility requirements, the 6 permanent exceptions (帳簿のみ保存の恒久特例), transitional measures for purchases from tax-exempt businesses, and storage requirements. This skill is not user-invocable — Claude loads it automatically when responding to input tax credit questions under the invoice system.

kazukinagata/shinkoku3652026年9月9日 更新

Fix Flutter home feed / main screen stuck on loading spinner after login when using Riverpod StreamProvider that watches GoRouter location changes. Use when: (1) Screen shows BrandedLoadingIndicator or CircularProgressIndicator permanently after successful auth redirect, (2) Widget watches a route-type-gating provider that returns AsyncValue.loading() intermittently, (3) Logs show route location oscillating between stale and current paths during post-login transition (e.g., /welcome/* after /home/0), (4) Provider chain has double-gate: widget gates on pageContext AND data provider also gates on pageContext. Distinct from riverpod-infinite-rebuild-loop (rapid rebuilds) — this causes permanent loading state, not infinite rebuilds.

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。

divinevideo/divine-mobile2662026年10月13日 更新

GitHub 解封 — 账号封禁/限制/恢复的领域操作系统。覆盖:(a) GitHub 官方政策体系 (TOS / 可接受使用政策 / Trust & Safety 执行模式 / 公开申诉路径 / 受制裁地区解读);(b) 封号原因诊断学 (spam / abuse / 制裁误标 / 2FA 丢失 / ToS 违规 / 账号劫持误判 / ban evasion 等子类型 + 症状→原因映射 + 自我分诊压测);(c) 申诉实操 craft (写一封能让 T&S 快速判误伤的英文申诉信 + 升级阶梯 + 法务介入边界 + Don'ts);(d) 制裁与合规硬边界 (OFAC SDN 名单 / 哪些国家或地区真不可达 / VPN 误判路径 / 中国大陆不是美国制裁地区的反复重申);(e) 中国大陆开发者特别处境 (sanctioned region 误标 + SMS 验证不支持 +86/+852 + Gitee/GitLab/Codeberg/JihuLab 备用迁移 + 私有自托管 Gitea/Forgejo);(f) 真实案例库 (~30+ 公开案例分类拆解:误伤 / 真违规 / 制裁误标三类各自赔率与申诉成功路径)。伦理锚绝不软化:不教 ban evasion / 不教撒谎式申诉 / 真违规承认改进 / 丢 2FA 无恢复因子则诚实告知 / 中国制裁误标靠申诉不靠换 VPN / 申诉 6 个月窗口必算清 / 约 3% (业内估) 真违规恢复 vs 约 79% (业内估) 误伤申诉成功率分层标。 (GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: false-positive / genuine violation / sanctions mis-flag, each with win-rate and appeal success path). Ethical anchors absolutely not softened: do NOT teach ban evasion (creating new accounts turns a temp ban into a permanent one — the single biggest mistake); do NOT teach social engineering or lying in appeals (misuse + actually confirms violation); genuine violations: admit + improve beats denial; lost 2FA + no recovery factor → do not pretend recovery is possible; China sanctioned-region mis-flag → fix via appeal, not repeated VPN switching; appeal form 6-month window must be counted carefully; historical 约 3% (业内估) genuine-violation recovery vs 约 79% (业内估) false-positive appeal success rate stratification must be honestly labeled. Anti-samples (explicitly describe harm, never endorse): developer permabanned for ban evasion / open-source team org-banned for personal attacks in public issues / cases where repeated VPN switching escalated risk-control severity.) Master OS — automated mastery of GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: fa

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。

swaylq/master-skill1492026年9月6日 更新

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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。

lilinji/GeneTind-Life-Skills142026年8月21日 更新

Positive Psychology according to Seligman: PERMA model, character strengths (VIA), gratitude exercises, flow theory, and resilience factors.

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。

ellmos-ai/skills82026年10月12日 更新

基于塞利格曼的积极心理学:PERMA模型、性格优势(VIA)、感恩练习、福流理论(Flow)与心理韧性要素。

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。

ellmos-ai/skills82026年10月12日 更新

Позитивная психология по Селигману: модель PERMA, сильные стороны характера (VIA), упражнения на благодарность, теория потока (Flow) и факторы жизнестойкости.

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。

ellmos-ai/skills82026年10月12日 更新

Psicología Positiva según Seligman: modelo PERMA, fortalezas del carácter (VIA), ejercicios de gratitud, teoría del flow (fluidez) y factores de resiliencia.

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。

ellmos-ai/skills82026年10月12日 更新

Positive Psychologie nach Seligman: PERMA-Modell, Charakterstärken (VIA), Dankbarkeitsübungen, Flow-Theorie und Resilienzfaktoren.

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。

ellmos-ai/skills82026年10月12日 更新

DeFi Specialist IA — Expert en finance décentralisée (Uniswap, Aave, Compound, liquidity pools, yield farming, impermanent loss)

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。

ziri22/agency-roster62026年7月1日 更新

paperkit

無料

Add drawings, shapes, and a consistent markup experience using PaperKit. Use when integrating PaperMarkupViewController for markup editing, adding shape recognition, working with PaperMarkup data models, embedding markup tools in document editors, or building annotation features that need the system-standard markup toolbar. New in iOS 26.

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。

JordanCoin/ios-skills-collection62026年9月10日 更新

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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。

peacezha/TRACE32026年10月11日 更新

skillify

無料

Codify the most recent successful /scrape flow into a permanent browser-skill on disk. Future /scrape calls with the same intent run the codified script in ~200ms instead of re-driving the page. Walks back through the conversation, synthesizes script.ts + script.test.ts + fixture, runs the test in a temp dir, and asks before committing. Use when asked to "skillify", "codify", "save this scrape", or "make this permanent". (gstack)

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。

mostafasudo/appilot32026年9月14日 更新

Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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。

peacezha/HPClaw32026年10月11日 更新