Results for “renderedcallback”

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Recover context from local AI conversation history with RecallBase. Use for same-day work summaries, resuming prior AI or coding sessions, or tracing a past decision to its source.

Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks.

Debug local web or Electron apps interactively using a persistent Playwright session with js_repl, enabling fast iterative UI debugging and visual QA.

Turn a weekly changelog markdown into a branded square video with animated UI mockups, voiceover, and captions.

Packages an existing talking-head, interview, or podcast video with timed, designed graphic overlay cards—kinetic titles, lower-thirds, data callouts, quotes, side panels, picture-in-picture—synced to the transcript, on a 16:9, 9:16, or 4:5 canvas.

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one. Source: github.com/emilkowalski/skills.

Restore working context saved earlier by /context-save. Loads the most recent saved state (across all branches by default) so you can pick up where you left off — even across Conductor workspace handoffs. Use when asked to "resume", "restore context", "where was I", or "pick up where I left off". Pair with /context-save. Formerly /checkpoint resume — renamed because Claude Code treats /checkpoint as a native rewind alias in current environments. (gstack)

Pauses mid-conversation to reassess direction, assumptions, and bias, then recommends whether to continue, pivot, or pause.

Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Trigger when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.

Retro

Generate a project-level context snapshot for resuming work in a fresh session

通用多轮迭代改进：对任意研究制品反复调用 /review → 解析反馈 → 修复 → 更新 wiki，直到达标

Engineering retrospective — generates a data-driven report of development velocity, commit patterns, hotspots, and team insights from git history. Saves results for week-over-week comparison.

Render videos from React/Remotion component code via inference.sh CLI. Pass TSX code, get MP4 output with configurable resolution, FPS, duration, and codec.

Resume work from previous session with full context restoration

Creates a technical journey retrospective document from a coding session, capturing decisions, tradeoffs, and debugging moments in a developer blog post style.

Generic webapp QA fallback — use only when no project-specific QA skill applies (project-local QA wins; native builds → mobile-emulator-test). Use when "QA the app", "test CRUD", or "smoke test". Monkey / guest vs logged-in → test-exploratory. Dead buttons → plan-stub-checker. Pixel diffs → test-visual-regression.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Post-epic review to extract lessons and assess success. Use when the user says "run a retrospective" or "lets retro the epic [epic]"

Reverse shell generation and listener management. Generates platform-specific reverse shell payloads (bash, python, php, powershell, java, ruby, perl, netcat, socat, msfvenom) and sets up listeners in the Kali container. Supports one-liner generation, encoded payloads for WAF/filter bypass, listener setup with session capture, and shell stabilization. Chains from /pentester, /metasploit, or /post-exploit when command execution is confirmed.

Mines git history and codebase to reconstruct the development lifecycle, identify sequential and parallel patterns, and produce actionable recommendations for future iterations.

Computes the Recall metric using torchmetrics, including configuration for binary, multiclass, and multilabel tasks.

Facilitate a structured sprint retrospective to surface insights and produce actionable improvements with owners and deadlines.

Use the status-briefing skill to run `pk-reconcile session-start`, then

Systematic debugging with persistent state across context resets

Packages an approved video project into a final deliverable, running preflight checks, rendering, and audio finishing.

`analysis-agent`/`task-agent`/`review-agent`: use for release identity, compatibility, exposure, stop, rollback, or recovery; skip pipeline-only and no-release work.

週次リフレクション（1週の振り返りサマリ）を生成するスキル。直近の完了週の日記から4要素（作業傾向/思考癖/繰り返す課題/CCアドバイス）を生成し、_INDEX気づきTop3はユーザー承認後に反映。ユーザーが「リフレクション」「今週の振り返り」「思考癖まとめて」と言った時、または /reflection を呼んだ時に発動。resume-sessionの検知提案からも起動される。

This skill should be used when the user asks to "reflect on skills from memory", "audit marketplace skills against memory", "从记忆中检查 skills 的问题", "反思并修改 skill", "apply memory feedback to skills", or wants to turn accumulated memory feedback about this marketplace's skills into concrete skill fixes. Reads the project's persistent memory, re-verifies each known skill problem against current code, then fixes the skill or corrects the stale memory.

Runs a full retrospective and dev cycle analysis, chaining /recall and /new-features to reconstruct what went wrong, extract lessons learned, identify rework patterns, and synthesize feature ideas from the findings.

Facilitate a structured sprint retrospective — what went well, what didn't, and prioritized action items with owners and deadlines. Use when running a retrospective, reflecting on a sprint, creating action items from team feedback, or learning how to run effective retros.

Restore working context saved earlier by /context-save. (gstack)

Re-onboard a churned customer with the same care they got the first time. Reads why they left and whether they left the door open, picks the ones worth winning back, and builds a warm re-onboarding sequence, not a "we miss you" discount blast. Built for any post-sale or growth team, customizable to your product and win-back window. Trigger on "win back churned customers", "re-engage a lost account", "build a win-back sequence", "which churned customers should we chase", "boomerang play", "re-onboard a customer who left", or any win-back question.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.