Results for “definition-of-ready”

Guides users to install and run the ai-ready skill for making repositories AI-ready with AGENTS.md, instructions, and CI workflows.

Evaluate whether a product is production-ready, publish-ready, or sellable-ready. Triggers: 'publish ready', 'ready check', 'readiness review', 'quality check', 'production ready', 'sellable ready', 'can I publish', 'release check', 'final review'.

Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".

Assess whether your product work is AI-first or AI-shaped, evaluate maturity across five key competencies, and get recommendations on which capability to build next.

Automatically detects your project stack and fills AI context slots, asking only for what it can't infer — your goal and the human 'why' — to reach 100% AI-readiness with minimal typing.

Internal technical readiness drill assistant for release and handoff.

Runs an adversarial code review with two blind judges analyzing the same code from opposing perspectives to find flaws before production.

Prepare implementation handoffs with states, flows, assets, edge cases, and acceptance criteria.

Stops fantasy approvals, evidence-based certification - Default to "NEEDS WORK", requires overwhelming proof for production readiness

Turns rough ideas into approved, decision-complete plans with validated structure before coding. Use when users ask in any language for planning, architecture, design direction, feasibility, value judgment, or whether a feature is worth doing before implementation. Not for bug fixes or small edits.

Use to build Science's data, code, and materials availability — mandatory deposition in approved repositories, accession numbers, a compliant data-availability statement, and materials/reagent sharing.

Friendly docflow readiness check: one status, one reason, and the exact next command. Use when asked if docflow is set up, ready, or "what do I do next".

Generates AI-ready context files for any codebase by auto-detecting the tech stack, scoring AI-readiness, and producing a portable .faf file that works across AI tools.

Broad risk assessment — key-person, technical, regulatory, competitive, financial, and execution risks beyond product/market

Turn a cold dial into a conversation. A permission-based opener plus ready objection turns for "not interested," "no time," "just send me info," and "we already use X," tuned to one persona. Built for B2B SDRs and full-cycle reps, customizable to your persona, offer, and dialer. Trigger on "write a cold call opener", "give me objection responses", "handle 'not interested'", "cold call script for this persona", or any live-dial prep.

Create a clear project status brief with progress, risks, blockers, decisions, and next actions.

Autonomously repairs failed task verification by choosing retry, decompose, prune, or escalate strategies before surfacing to the user.

Runs and writes tests, verifies behavior, and orchestrates two-pass TDD across scoped modes, blocking on quality gates and never editing production code.

Adversarially verify an implementation against its objective, acceptance criteria, definition of done, and prohibitions using fresh evidence. Use for completion gates, release readiness, or independent verification after implementation and review.

Scaffolds a per-task verification skill for a repo, including a dev-local launcher, a browser driver, and a verification SOP that spawns a sub-agent to drive the app and produce proof.

当用户提出一个想法或诉求时，通过对话挖掘真实意图、明确边界，提炼成清晰、可执行的概念。

Pragmatic coding standards - concise, direct, no over-engineering, no unnecessary comments

当需要进入高效学习、创作或问题解决的心流状态时，调用此模型作为环境与心理准备框架