29 件 ・ 関連度順
概要と使いどころ
Toggle the badges-page Honesty Mode build-time flag on or off. ON makes the README badge generator emit direct /badges/_assets/<handle>/<file>.svg URLs (no Cloudflare Worker, no ?repo= validation). OFF restores worker-validated URLs. Use when the user says "/honesty-mode on", "/honesty-mode off", "turn honesty mode on/off", or asks for the current honesty-mode 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。
当用户问怎么真诚沟通/拒绝别人/给反馈/不想说场面话、或发现自己在隐瞒时调用。 核心理念: 撒谎会先骗到自己(费曼: 你最容易愚弄的人是你); 彻底诚实=所想与所说一致; 具体表扬、一般批评; 秘密越少快乐越多。 不适用于: 需要外交辞令的谈判策略(可以诚实但不必全说)。 Triggers: 诚实/沟通/拒绝/批评/表扬/秘密/场面话/honesty/communication/feedback
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。
Pick the chart the data and the point actually need — the question-to-chart mapping (comparison, trend, composition, distribution, relationship), the honesty rules (axes, baselines, dual-axis traps), and the one-chart-one-point discipline. Use when asked what chart should I use, make this data visual, why does this chart feel misleading, or fix this graph for the deck. Produces the chart verdict with its reasoning, the honesty checklist applied, and the labeling that lets the chart travel without its author.
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。
Epistemic transparency — acknowledging uncertainty, flagging limitations, avoiding overconfidence, and communicating what is known, unknown, and uncertain with proportional confidence. Maps the HEXACO personality dimension to AI reasoning: truthful calibration of confidence, proactive disclosure of gaps, and resistance to the temptation to appear more certain than warranted. Use before presenting a conclusion, when answering questions where knowledge is partial or inferred, after noticing a temptation to state uncertain information as certain, or when a user is making decisions based on provided information.
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。
Prove a RuView result is real — run the deterministic SHA-256 proof and the witness bundle (ADR-028), and lint any claim for MEASURED-vs-CLAIMED honesty.
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。
A short self-bias checklist to run at the START of any investment research task (stock screen / sector study / company deep-dive). Four biases that systematically warp AI research — leader-bias (only big caps), English-bias (miss JP/KR/TW players), narrative-bias (chase concept labels), confirmation-bias (only bullish evidence) — plus recency-bias. Load this first, then research with the corrections in mind. Not a workflow, just a 60-second attitude reset that materially improves coverage and honesty.
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。
Author an eval for an existing skill from its REAL usage history, not its spec. Mine invocations from the brain's conversation archive (conversations/) and per-harness session transcripts — a user correction after an invocation is the gold signal — then synthesize an eval_contract plus 4-8 replayable cases with honesty labels (SPEC-DERIVED vs HISTORY-IMPLIED) and stage the result at skills/<name>/eval/autobench-<date>.md as PENDING-HUMAN-APPROVAL. Never rewrites SKILL.md. Ships two guard companions: panel integrity (multi-model judging must prove each provider actually responded) and the fail-improve taxonomy (logged LLM-fallback cases convert to deterministic code over time).
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。
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
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。
Use when replacing a seat's occupant (rebuild/handover/swap), reasoning about stable-seat-identity vs fluid-occupant-identity, choosing an old-occupant disposition (retire/advise/shadow), or recording provenance for an occupant change. Two independent outcomes (continuityOutcome + seatBindingOutcome) and the 5 failure modes that prevent silent dishonesty.
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。
Use when creating, refreshing, packaging, inspecting, promoting, or deprecating a named per-seat starting point — Agent Starter manifest authoring, the 6-state lifecycle (captured → named → inspectable → used → promoted → deprecated), provenance honesty, and refusal rules. NOT a VM image; a managed starting point composed from agent role + startup context + optional native session source + provenance.
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。
Use when reasoning about the rig lifecycle operations family (create / start / stop / resume / restore / snapshot / release / unclaim / destroy), reading or trusting `rig ps` / lifecycle projections after recovery, or designing proof for a lifecycle scenario. Covers the 4 failure modes (auto-restore creates partial rig; projections report healthier than reality; provider auth treated as impl work; resume succeeds for one runtime fails another) plus the restore-honesty rule (failed resume is FAILED loudly — no auto fresh fallback).
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。
Use when the user asks to "build programmatic SEO pages", "generate pages at scale", "rank on a high-authority third-party site", "borrow domain authority", "build a vs / alternative page", "do local SEO", "optimize a Google Business Profile", or "fix NAP" — one page-build router with four modes: programmatic (template × dataset systems), parasite (barnacle publishing on Medium/Reddit/LinkedIn/GitHub), comparison (vs / alternative pages in four formats), and local (GBP + NAP + citations + location pages), each with its own thin/duplicate, honesty, or reputation-abuse guardrail. Not for finding what to target — use keyword-research or content-gap-analysis; not for drafting one standalone article — use content-writer; not for scoring a page for publish — use content-quality-auditor. 程序化SEO/批量页面/寄生SEO/借势权重/对比页/vs页/替代页/本地SEO/谷歌商家档案/NAP一致性
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。
FAIR-aligned exposure quantification: turns a pile of recon findings into a defensible 0-100 + A-F org risk score (Likelihood x Impact, three ownership-aware factors: exposure/threat/impact), an ownership + proof demotion cap so unproven or weakly-owned findings can't inflate the number, a $-denominated FAIR loss-magnitude estimate (IBM/Ponemon per-record cost bands, cross-source record dedup, threat-factor annualization), attack-path amplification (curated red-team chain catalog + generic graph-walk engine, with a kill-chain vs shared-fate honesty gate), and a board-ready one-pager deliverable (hero $ + letter grade + top-3 findings + top attack path + the ask). Extends osint-methodology's severity rubric and client deliverable templates with quantification. Passive analysis only -- operates on findings already collected, no target traffic, no API keys. Use when asked to score risk, quantify exposure, estimate breach cost, build a board report, translate technical findings to dollars, or explain why a grade or dollar figure came out the way it did.
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。
Role profile — a reviewer who is fact-seeking, bedrock-seeking, honest, and rejecting. Demands that arguments rest on small facts that cannot be wrong (not on stacked assumptions dressed up as foundation), and that deliberately-unclear concepts be quarantined — never leaked into solid layers, never mixed with each other. Catches the failure mode where designs ship after partial grounding: most of the spec researched, the design feels finished, and the unresearched remainder holds the deal-breaker. Invoke with `/pedantic <target>` (e.g. `/pedantic review this design doc`, `/pedantic review the SDK design`, `/pedantic review this PR`). Probes cover logical structure (definitions, assumptions, boundaries, contradictions, unfalsifiability, vague quantifiers, counterexamples), epistemic honesty (researchable vs. discoverable-only-by-doing), bedrock integrity (assumed-bedrock, leaked uncertainty, mixed unclarity), and design pathology (YAGNI, wrong-layer abstraction, unclear responsibility, fragmentation, over-engineering). Use when you want a hard critique of a plan, design doc, technical doc, code change, or PR description — not a copy edit, not a vibe check.
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 one long video, podcast, or stream transcript into 8-12 short-form clips — each with a hook line, cut timestamps, captions, and a platform note for TikTok/Reels/Shorts — plus an honesty gate that kills clips that misrepresent the source. Use when someone says 'clip this podcast', 'make shorts from my video', 'what's clippable here', or runs a clipping side hustle. Produces a ranked clip sheet ready for an editor or a clipping app.
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 a folder of accumulated documents into one decision-ready brief — the skim-map pass over the pile, the extraction against the brief's actual questions, the conflict reconciliation when documents disagree, and the provenance trail back to sources. Use when asked read all this and tell me what matters, synthesize this folder for the new lead, turn these 20 docs into a brief, or what does all this material actually say. Produces the pile map, the question-driven extraction, the reconciled brief with per-claim sources, and the didn't-read honesty ledger.
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。
Use when revising an ACM CCS paper for a precise threat model, calibrated attack/defense claims, 12-page ACM sigconf compression, double-blind wording, adaptive-evaluation honesty, and the security house style that survives an adversarial SIGSAC program committee.
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。
Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.
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。
Applies anti-sycophancy checklist to override agreement bias. Use when analyzing contested claims or avoiding socially convenient but inaccurate conclusions.
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。
Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.
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。
Expert in brutally honest, self-deprecating marketing that converts. Covers transparent messaging, vulnerability as strategy, "we're not for everyone" positioning, and turning weaknesses into strengths. Knows when honesty builds trust and when it backfires. Use when "anti-marketing, honest marketing, brutally honest, we're not for everyone, transparent, no bullshit, self-deprecating marketing, " mentioned.
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。
Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.
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。
Use when the user asks to "build programmatic SEO pages", "generate pages at scale", "rank on a high-authority third-party site", "borrow domain authority", "build a vs / alternative page", "do local SEO", "optimize a Google Business Profile", or "fix NAP" — one page-build router with four modes: programmatic (template × dataset systems), parasite (barnacle publishing on Medium/Reddit/LinkedIn/GitHub), comparison (vs / alternative pages in four formats), and local (GBP + NAP + citations + location pages), each with its own thin/duplicate, honesty, or reputation-abuse guardrail. Not for finding what to target — use keyword-research or content-gap-analysis; not for drafting one standalone article — use content-writer; not for scoring a page for publish — use content-quality-auditor. 程序化SEO/批量页面/寄生SEO/借势权重/对比页/vs页/替代页/本地SEO/谷歌商家档案/NAP一致性
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。
Use this skill when writing, rewriting, or improving marketing copy for any page (homepage, landing page, pricing, feature, product, or about page). This skill produces clear, compelling, and testable copy while enforcing alignment, honesty, and conversion best practices.
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。