Results for “intent”

Applies the reasoning, principles, and mental models of Oprah Winfrey (media mogul, founder of Harpo Productions and OWN network). Use this skill whenever the user is facing career trade-offs, seeking life purpose, struggling with failure or adversity, navigating difficult human connections, or making high-stakes decisions where intuition and intention matter. Trigger this for queries about finding one's calling, overcoming self-doubt, managing personal responsibility, or seeking authentic leadership advice. Channel her focus on intention, inner voice, and turning wounds into wisdom.

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Applies the rigorous analytic and moral philosophy of Elizabeth Anscombe (British analytic philosopher, virtue ethics, Intention). Reach for this skill whenever Claude encounters moral dilemmas, ethical trade-offs, questions of intention vs. foresight, or consequentialist/utilitarian reasoning. Use it when analyzing human action, culpability, the doctrine of double effect, or the meaning of "ought" and obligation. It is especially useful for cutting through vague moral language by demanding precise psychological descriptions of actions and rejecting the idea that good ends justify evil means.

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Research, expand, and cluster keywords for content strategy. Use when planning content topics, building keyword lists, expanding seed keywords, clustering by topic and intent, or mapping keywords to funnel stages. Triggers on "keyword research," "keyword expansion," "keyword clustering," "content topics," "what to write about," "topic ideation," "content planning," "6 circles method," "seed keywords," "keyword difficulty," "search volume," "intent mapping," "pillar content strategy," or "content calendar planning." For SEO optimization and auditing, see seo-and-aeo-strategy.

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Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.

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Extract creative intent from images into executable build specs. Activates on images + build intent, "image to mission", "i2m", or capturing visual energy in code/design.

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Anoma intent-centric architecture for cross-chain obstruction passing with Geb semantics and Juvix compilation

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Interrogate the user before implementing a non-trivial or ambiguous ask, converging on shared intent. Use when the user says "grill me", when an ask admits multiple interpretations, or before any sizable piece of work whose intent isn't fully clear.

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Summarize the currently staged Git changes as a human-readable, intent-grouped narrative. Use when the user wants a concise and brief report of what changed and why. Optionally can check the diff for intent coherence and show a risk and blast radius report.

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Use when searching for buying signals, detecting intent data, scoring prospect readiness, or monitoring accounts for trigger events. Triggers: 'scan for signals', 'find buying signals', 'who is ready to buy', 'intent signals', 'signal scoring', 'account signals'.

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AI-PLCのステータス点検（intent・backlog・Registry の食い違い）。Jev 実験版を入れたときだけ使える。

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AI-PLCの進行中に、ユーザーの「ここをこうしたい」を命令ではなく相談として受け、今のLayer（intent・backlog）と照らして「却下／今のタスク内で修正／Re-Inception／Re-Collection／いつかやる」に振り分け、所感と次に打つコマンドを返す（読み取り専用・実行しない）。「どう思う？」「これやるべき？」「Inceptionからやり直すべき？」「次どのコマンド打てばいい？」で使う。

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AI-PLCのステータス点検。intent.yaml・backlog.yaml・Registry の食い違い（閉じ忘れ・Layer不明・停滞・Registry漏れ）を読み取り専用で洗い出し、人が承認した行だけ反映する。「ステータス点検して」「閉じ忘れを探して」「食い違いを見て」で使う。Jev 実験版（--with-jev）を入れたときだけ使える。

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Use at the start of any session on a project with a build graph (`.hedgehog/hedgehog.db`), and again at every claim/dispatch/verify cycle within it. Owns consuming the build graph — claiming task packets, delegating each to the layer's agent, running `hedgehog verify` to gate the commit, recording debt and decisions, the intent check at an intent's last layer, and when to clear context. Not for a build agent handed an already-claimed packet — that agent never claims, dispatches, or verifies; this skill is the orchestrating session's own.

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Design intentional internal link graphs for SEO, UX, and LLM-readable sites. Use this skill when the user asks for links between short briefs, longform articles, topics, projects, author pages, breadcrumbs, source trails, related stories, orphan-page checks, overlink checks, anchor intent, or validation that a link graph reinforces the canonical content model without creating duplicate story bodies or hidden links.

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"Design conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.".

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Account-based marketing for B2B SaaS. Use this skill to build a target account list, tier it 1:1 / 1:few / 1:many, size it against sales capacity, turn intent and engagement signals into plays, write the multi-channel orchestration contract each tier runs on, and measure the program in account coverage, penetration and pipeline instead of MQLs. Also triggers on: ABM, account-based marketing, target account list, TAL, named accounts, account tiering, 1:1 ABM, one-to-few, programmatic ABM, account selection, ideal customer profile fit, intent data, buying signals, 6sense, Bombora, Demandbase, account penetration, account coverage, sales and marketing alignment on accounts, enterprise account program.

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Detects code quality vulnerabilities in mobile apps (Android/iOS). Trigger on: SQL injection in SQLite, JavaScript injection in WebViews, intent injection, unsafe deserialization, NSKeyedUnarchiver, NSCoding, Java serialization, Parcelable, buffer overflow, JNI native code, PIE disabled, NX disabled, stack canary absent, RELRO, ARC disabled, third-party library CVE, vulnerable dependency, outdated SDK, targetSdkVersion, update enforcement missing, implicit Intent, URL loading in WebView, object persistence, memory corruption, OWASP dependency check. Covers MASVS-CODE-1/2/3/4.

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Unity procedural generation design-to-code translation. Noise-based terrain/placement, tile & grid systems, dungeon/room generation, seed & reproducibility, content budget & constraint systems, runtime vs baked generation. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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Unity game loop and progression design-to-code translation. Core loop scaffolding, session lifecycle, win/lose condition architecture, meta loop hooks, tunable difficulty, pacing & encounter timing. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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Unity level design-to-code translation. Trigger & event architecture, encounter design contracts, checkpoint & respawn, cinematic & scripted sequences, environmental storytelling hooks, level streaming & loading seams. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/ DESIGN HOOK. Based on Unity 6.3 LTS.

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Unity NPC behavior design-to-code translation. Perception system architecture, decision layer patterns, action execution pipeline, faction & relationship systems, NPC memory & forgetting, crowd & squad coordination. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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Unity UI/UX pattern design-to-code translation. Screen flow architecture, View/ViewModel separation, HUD architecture, feedback & juice systems, dynamic list/grid views, transition & animation contracts. UI Toolkit only. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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Creates accurate frontend implementations from visual references while maintaining design consistency. Use when user provides Figma URLs, screenshots, design images, requests visual implementation from reference, or asks to build UI matching a design. Automatically checks existing design intent patterns before implementation.

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Diagnose search-experience and intent mismatches using SERP page types, user stories, and persona scoring. Use when ranking problems appear intent- or layout-driven.

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