Results for “induction”

Design motivation systems for products and teams using Autonomy, Mastery, and Purpose (AMP) to drive intrinsic engagement.

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.

Team-Wiki Ingest

Learn best practices for writing effective AI video generation prompts, covering shot types, camera movements, lighting, style keywords, and model-specific tips for Veo, Seedance, Wan, Grok, and others.

Design motivation systems using Autonomy, Mastery, and Purpose (AMP) for products and teams. Use when the user mentions "intrinsic motivation", "gamification isnt working", "team incentives", "autonomy", "mastery", "purpose-driven", "employee engagement", or "reward systems". Also trigger when designing onboarding progression systems, fixing broken gamification, or building team structures that sustain high performance. Covers why carrot-and-stick fails and how to build progress systems. For habit-forming product loops, see hooked-ux. For retention behavior design, see improve-retention.

Start, query, and stop a TAO inference microservice for a specific network architecture by delegating container execution to the appropriate platform skill.

Upload offline conversions, enhanced conversions for leads, click conversions, and Google Analytics events using the Data Manager API /v1/events/ingest endpoint.

Transforms vague UI ideas into polished, Stitch-optimized prompts by enhancing specificity, adding UI/UX keywords, injecting design system context, and structuring output for better generation results.

SQL injection occurs when untrusted user input is interpolated directly into database queries, allowing attackers to alter query logic. Detect via single-quote errors, boolean-based blind responses (AND 1=1 vs AND 1=2), time-delay payloads (SLEEP, WAITFOR), UNION column enumeration, and error messages from MySQL, Oracle, MSSQL, PostgreSQL. Tools: sqlmap, sqlbftools, Burp Suite, wfuzz with SQLi fuzz strings.

Starts a session by initializing a local database, selecting or creating a workspace and outcome, then routing to the relevant phase reference.

Captures ideas, tasks, or issues during a GSD session as structured todos for later work, enabling a thought-to-capture-to-continue flow without losing context.

Learn and apply prompt engineering techniques for LLMs, image generators, and video models using the inference.sh CLI.

Multimodal proposal brief intake — turns text, audio, or video into a structured, completeness-checked brief.md. Use when the user pastes a client brief, drops a voice memo or call recording, shares a video brief, asks to 'intake a proposal', 'structure this brief', or starts a new proposal run. Triggers: 'intake this brief', 'transcribe this recording', 'structure the brief', 'new proposal from voice memo', 'parse this RFP brief'.

2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection

Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.

当设定个人或工作目标，希望目标本身能带来持续的内在动力和满足感时

Transforms vague UI ideas into structured, Stitch-optimized prompts with design system context and UI/UX keywords.

Implements a piece of work from a spec or ticket set. Use when the user says "implement this spec", "work the tickets", or wants code written from an existing plan.

Analyzes prompt injection, retrieval poisoning, memory contamination, planner drift, and tool-boundary abuse in agentic systems, mapping trust boundaries and proving exploit chains.

Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.

JNDI injection playbook. Use when Java applications perform JNDI lookups with attacker-controlled names, especially via Log4j2, Spring, or any code path reaching InitialContext.lookup().

Python SDK for inference.sh - run AI apps, build agents, and integrate with 150+ models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python

Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.

Imports external plan files into a GSD-structured project, detecting conflicts against existing roadmap, requirements, and locked decisions before writing a validated PLAN.md.

Trigger: TDD, test first, unit testing, integration tests, mock assertions, test-driven dev. Scope: Writing test assertions before coding features, testing paradigms. Boundary: Excludes UX aesthetics or continuous deployment settings.

Generate invoice generator operations. Auto-activating skill for Business Automation. Triggers on: invoice generator, invoice generator Part of the Business Automation skill category. Use when working with invoice generator functionality. Trigger with phrases like "invoice generator", "invoice generator", "invoice".

Guided first-run that produces a real verified win in under five minutes using the skill library on a seeded offline fixture. Load when a new user asks how to start, run the demo, try agent-loom, or get a quick win. Also triggers on "quickstart", "first run", "demo agent-loom", "try the skills", or onboarding to the library. Zero external credentials required. Idempotent — safe to run multiple times.

Design first-run experiences that get users to value quickly without overwhelming them.

Cross-runtime 2-stage pipeline for Claude Code, Codex/OMX, and Gemini/Antigravity/OMA: trace causal hypotheses, inject evidence into deep-interview style requirements crystallization, then hand off to the right runtime planner/executor.

Generates a comprehensive developer onboarding guide from a codebase, covering tech stack, setup, architecture, conventions, and troubleshooting.

Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.

Onboarding and activation optimization for Nick's products. Use when improving first-run experience, reducing drop-off, guiding users to value faster, or cleaning up empty states, setup friction, and early confusion.

Score the experience a new customer actually has, not just whether they activated. Grades the first 90 days on the moments that make someone feel taken care of, finds where the welcome goes cold, and hands back a scored audit with the specific fixes. Built for any post-sale team, customizable to your product and lifecycle. Trigger on "audit my onboarding", "score our onboarding experience", "why do new customers churn early", "grade our first 90 days", "where does onboarding go cold", "is our welcome any good", or any onboarding-quality question.

Derive a portable product-idea kickoff prompt from the invoking repository for use with $idea-scope-brief in a different repository. Use when a repo suggests an adjacent product, SaaS, devtool, library, workflow, or experiment worth briefing elsewhere, but the user wants an idea prompt rather than code extraction or repo creation.

Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers.