Results for “anchoring-bias”

Skeptical pushback on visual placement — both density and quality. Reads the annotated outline plus the visuals manifest and asks (a) whether the article hits the density target from editorial-principles-visuals.md, (b) whether each [VISUAL:...] earns its place, (c) whether sections without one would benefit. One revision pass on FAIL (BLOG_AGENT_VISUALS_REVISION_BUDGET, default 1).

安室透（少年推理漫）认知与表达框架（压缩蒸馏）：三重身份张力、波本梗、服务生伪装 触发：名侦探柯南 等。虚构；禁止犯罪教唆

Request a re-anchoring block: your goal, standing constraints, budget, and the actions you already completed this session. Call this whenever you feel uncertain about what you were doing, suspect you lost context, or before any consequential action.

Provides a rigorous thinking partner profile that challenges assumptions, calibrates claims to evidence, and improves decision quality under uncertainty.

Anchors work at the current moment and places events as spatial distances ahead or behind to improve temporal reasoning.

Use this skill for information architecture, internal links, hub pages, anchor text, crawl depth. Trigger when the task involves seo work related to Internal Linking Ia, production implementation, audits, debugging, strategy, or validation.

Use only for developer-facing products; position against alternatives by workflow, ecosystem, trust, and switching cost

Design metacognitive checkpoints that prevent AI-assisted learning from bypassing genuine understanding. Use when students use AI tools and may overestimate their own comprehension.

Trigger: a11y, accessibility, ARIA, screen reader, contrast, keyboard, tap targets, focus. Scope: Audit web interface accessibility compliance (WCAG AA). Boundary: Do not use for general backend logic or CSS styling aesthetics.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems by improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Audit and fix HTML accessibility issues including ARIA labels, keyboard navigation, focus management, color contrast, and form errors.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Navigate the technology adoption lifecycle from early adopters to mainstream market. Use when the user mentions "crossing the chasm", "beachhead segment", "whole product", "early adopters vs. mainstream", "tech go-to-market", "bowling pin strategy", "technology adoption lifecycle", or "pragmatist buyers". Also trigger when a startup has early traction but struggles to grow beyond initial users, or when planning go-to-market for technical products. Covers D-Day analogy, bowling-pin strategy, and positioning against incumbents. For product positioning, see obviously-awesome. For new market creation, see blue-ocean-strategy.

Audits hidden assumptions in decisions by classifying them into four types, ranking by fragility and impact, and rebuilding conclusions from verified premises. Auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Audits decisions and situations for operating psychological biases using Munger's 25 tendencies framework, producing a structured analysis with countermeasures.

Harness Strategy

Optimize post-signup onboarding, user activation, first-run experience, and time-to-value with actionable audits and flow designs.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Use to design VIP or tiered support programmes and to test whether higher tiers actually deliver better outcomes. Trigger for "VIP support programme", "service tiering", queue priority for premium customers, entitlement vs priority, tier inflation, or "does our enterprise tier get faster support".

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Every metric encodes an opinion about which mistake hurts.

Evaluates social bias in question-answering models using the BBQ benchmark, measuring accuracy and a bias score across ambiguous and disambiguated contexts to reveal reliance on stereotypes.

Give a decisive, project-grounded point of view in the subject's own shape: a graded verdict on an external-adoption question, a holistic take on a document, or a position on a user-supplied approach set. Use for a solo POV, a mid-session second opinion, a named-peer cross-check, any request to consult other models or reconcile their opinions, an `oracle` panel, or a correction-cost-gated proactive cross-check offer. Not for findings review (use ce-doc-review), neutral explainers, or generating options (use ce-ideate or ce-brainstorm).

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

安欣（刑侦剧虚构）认知与表达框架（压缩蒸馏）：理想主义耗损、程序正义执念、白发象征… 触发：狂飙 等。禁止刑侦违法教程；虚构

Post-draft pass that expands a drafted article to capture the FULL keyword family — keywords the page already or could rank for, plus the Ahrefs Content Gap (keywords competitors rank for but we don't) — by weaving the worthwhile ones in as natural added paragraphs/sections. NOT keyword stuffing. Triggered after /draft, before /quality-check.

Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Framework-driven copywriting for ads, landing pages, emails, sales pages, and CTAs. Includes AIDA, PAS, BAB, 4Ps, StoryBrand, QUEST, FAB, and more. Use when writing conversion-focused copy, ad creative, headlines, email sequences, sales pages, or when the user mentions copywriting frameworks, persuasive writing, or direct response copy.

Anki spaced repetition learning system reference. Covers the science of SRS and SM-2 algorithm, card design principles, optimal deck settings, FSRS scheduler, study workflow, essential add-ons, custom templates, filtered decks, and AnkiConnect API.

Manage Binding entities — scoped, temporal, many-to-many relationships between v2 entity surfaces. Use when a relationship needs scope, time, or its own attributes — e.g. 'Alice is the tech lead for project X from Jan to June' or 'the security gate applies to this release WorkItem only on the main branch'.