Results for “bec”

Decides how far ahead to plan, what to discount future payoffs by, and which backlog items can be dropped without analysis - using receding-horizon planning, an explicit discount factor, and branch-and-bound pruning against the incumbent. Use when building a roadmap, prioritising a backlog, arguing about short-term versus long-term, setting quarterly or annual plans, or when planning has become an end in itself.

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Use when a live-action beat becomes the 11-block cinematic prompt — lens, lighting, negatives. Triggers 'cinematic prompt', 'film-grade scene'. Animated → pixar-storyteller; 12-block → scene-expander.

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Use when an idea becomes a Pixar-style animation prompt — character sheet, scene, image, video; emotional beat, want, obstacle. Triggers 'Pixar prompt', 'animated scene'. Live-action → video-director.

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Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

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Map existing materials into a first knowledge record, or investigate a subject's history in depth. Use whenever the user asks to map, survey, go through, reconstruct or investigate what already exists - folders of documents, decision records, meeting notes, emails, exports, code - or wants a starting record built from existing materials, even when the word 'record' is never said: consult this before listing or reading the files yourself, because a map has an agreed scope, a protocol and a report. Also, once, at a suitable moment, to offer the starting choices where a workspace has no record and the work is clearly ongoing - never on a greeting. Learning while working needs no map. Requests come in any language.

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Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you don't trust.

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Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

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Build an evidence-backed working model of an existing codebase. Use when you must orient in a large or unfamiliar repository; explain architecture or a subsystem; trace a request, runtime, control, or data flow for a concrete question or bug; analyze a branch, commit, diff, or pull request for behavioral impact and blast radius; or assess AI-generated or changed code against requirements, contracts, invariants, tests, and runtime evidence. Default to read-only investigation. Do not trigger only because a coding task touches an existing repository; use when understanding or verification is the requested outcome or a substantial prerequisite.

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Use when adding or reviewing macOS user notifications — UNUserNotificationCenter permission flow, categories and action buttons, click routing through the delegate, foreground presentation, and rules that keep notifications from becoming spam.

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Produces a deep, honest peer-review of how someone uses Claude Code by statistically analyzing their local session data (~/.claude/usage-data/ and ~/.claude/projects/). Trigger whenever the user asks to review, analyze, audit, or critique their own Claude Code usage, workflow, habits, or skill level — including phrases like "analyze my cc usage", "review my cc sessions", "peer review my cc workflow", "deeper than /insights", or any ask for an honest audit of their AI workflow. Also covers portfolio/hiring-manager framings (e.g. "portfolio for Anthropic/OpenAI/xAI"), but ALWAYS ask the user in Step 0 which version to build (self / hr / both) before running — never silently produce an HR report, because that version goes to outsiders and needs explicit privacy setup. The HTML report is laid out ledger-first for SELF (opening band, output/team/leak/trend ledgers, then peer review, 9-dim scoring, try-this-week, case study, claim-indexed evidence). The HR variant is a recruiter version v1: identity card, earned badges (threshold-based, earned-only), allowlist-filtered output ledger, one case study, and a methodology & scope disclosure — no scores, no peer-review memo, no charts.

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Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.

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Use when PostgreSQL logical replication slots retain WAL, become orphaned or invalid after switchover, or must be proven synchronized and usable before failover.

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Merges mature lessons from a domain memory file into its instruction file. Syntax: `/memory-merger >domain [scope]` where scope is `global` (default), `user`, `workspace`, or `ws`. Use when a domain memory file has accumulated lessons that should become permanent instructions.

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Discipline for repairing a false claim once it has propagated: select what depends on it, produce a replacement, and accept with an expiring verdict. Trigger when: - A claim, citation, premise, or documented fact is found wrong and its downstream consequences must be traced and fixed. - A refutation, a failed re-run, a retracted external source, or a human correction lands against something already closed or already promoted. - Prompt contains: /remediation, remediation, retraction, false claim, propagated error, scrub, correction propagation, born-false, became-false, currency verdict, impeachment queue.

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Control and interact with a live browser session on any scraped page — click buttons, fill forms, navigate flows, and extract data using natural language prompts or code. Use when the user needs to interact with a webpage beyond simple scraping: logging into a site, submitting forms, clicking through pagination, handling infinite scroll, navigating multi-step checkout or wizard flows, or when a regular scrape failed because content is behind JavaScript interaction. Also useful for authenticated scraping via profiles. Triggers on "interact", "click", "fill out the form", "log in to", "sign in", "submit", "paginated", "next page", "infinite scroll", "interact with the page", "navigate to", "open a session", or "scrape failed".

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Wardley Mapping for strategic positioning — map your value chain from customer need to underlying components, plot where each component sits on the evolution curve (novel to commodity), and spot the strategic plays that movement creates. Use this skill when someone wants to understand where their industry is heading, whether they're building things they should be buying, where competitors are vulnerable, what's about to become commoditised, or why their competitive advantage is eroding. Triggers on questions about build-vs-buy, component evolution, value chain analysis, commoditisation risk, or strategic positioning relative to market movement. Three modes — full diagnostic (build a map from scratch), review (update positions and reassess), and alert triggers (set tripwires for when components move). Based on practice by Eterdis (eterdis.com).

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Teach software development through active project work while still producing a working result, maintaining bilingual English and Chinese project documentation, protecting private context, and publishing reviewed updates to GitHub only after confirmation. Use when Codex helps the user create, build, extend, debug, refactor, document, publish, or understand a software project and the user's goal includes learning, mentorship, guided implementation, pair programming, understanding the code, or becoming able to do similar work independently.

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Explain what the project is and does by design, what it is becoming, the value being built, its architectural trajectory, and where design intent and built reality diverge; publish a retained, ledger-recorded report when the operator requests a high-altitude perspective.

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Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

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Detect compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.

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Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.

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Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.

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Resolve complex or high-impact problems when the cause, solution path, requirements, or proof boundary is genuinely uncertain. Use when work needs evidence-led diagnosis, consequential design or implementation, or a completion audit; do not trigger merely because work has multiple steps, or for simple facts, fully specified routine changes, or pure creative generation.

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Run Telegram as a scoped auto-reply assistant grounded in the owner's vault and written in their voice: whitelisted low-stakes chats are answered autonomously, while anything financial, committing, sensitive or from an unknown contact becomes a draft for the owner. Triggers: "handle my telegram", "reply for me in <chat>", or a new message in a whitelisted chat.

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