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Found 73 Skills
Create session retrospective with AI diary and lessons learned. Use when user says "rrr", "retrospective", "wrap up session", "session summary", or at end of work session.
Generate LESSONS.md retrospective files that capture institutional knowledge, especially failures. Use when closing out journalism projects, investigations, events, or publications. Includes templates for research projects, event post-mortems, editorial tools, and publications.
Generates a detailed project explanation and retrospective (FOR_USER.md) to help the user learn from the project. Use this skill when the user asks to explain the project, asks "what did we just build?", or invokes the skill to generate a learning resource after a coding session.
Analyze git commits within a specified time range and generate a work retrospective report. Trigger words: retrospective, review commits, git review, what did I do today, work summary, daily review, retrospective
Edit and design the materials provided by users (webpage URLs / PDFs / DOCX files / Markdown / plain text / screenshots / pasted content) into a beautiful, offline-accessible and shareable **single-file HTML web article**. Based on the reacticle component protocol: instead of writing raw HTML/CSS manually, use semantic components + theme-constrained Raw free layers; follow the small harness workflow of source → planning → double confirmation → generation → final review → repair, and produce long articles with 100% information retention by default. Trigger scenarios: convert URLs/PDFs/DOCX files/articles into web articles / long-form articles / briefings / explanatory articles / visual articles / tutorials / review and retrospectives / program analyses, with triggers like 'render this as a beautiful web article / turn this into a web article / generate a shareable HTML long-form article / reacticle article'. Only generate articles, not backends, forms, dashboards, product prototypes or general web apps.
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas.
Create a personal GitHub coding retrospective from a date range and turn it into a short Markdown review. Research commit activity across accessible public and private repositories through the authenticated gh CLI, understand what the relevant repositories and subsystems are for, and write a prose retrospective with stats and highlights. Use when the user asks for a commit review, coding recap, engineering retrospective, GitHub activity story, weekly/monthly/yearly highlights, or a written summary of what their commits achieved.
Biennale Yellow — Solar yellow on warm parchment with deep indigo serif and atmospheric sun-glow gradients. Anything that should feel like an art-biennale poster or a museum's annual programme: exhibition decks, arts-institution announcements, design conference brochures, curatorial pitches, literary publications, studio retrospectives.
Best practices for contributing code to TensorRT-LLM. Covers the official contribution process (issue tracking, fork workflow, DCO signing), coding guidelines, implementation workflow, common mistakes, testing strategy, commit hygiene, and review readiness. Incorporates rules from CONTRIBUTING.md and CODING_GUIDELINES.md plus lessons distilled from real PR retrospectives. Use when implementing new features, optimizations, or bug fixes in the TensorRT-LLM codebase.
Skills retrospective and improvement. Use when: - User asks to "review", "retrospect", "summarize" or "复盘" skills - User wants to analyze skills issues from the conversation - User requests skills optimization or improvement - End of conversation or after significant skill usage
Facilitate effective retrospectives to capture lessons learned, celebrate successes, and identify actionable improvements for future iterations.
(Industry standard: Routing Agent / Orchestrator Pattern) Primary Use Case: Analyzing an ambiguous trigger and routing it to one of the specific specialized implementations. Routes triggers to the appropriate agent-loop pattern. Use when: assessing a task, research need, or work assignment and deciding whether to run a simple learning loop, red team review, dual-loop delegation, or parallel swarm. Manages shared closure (seal, persist, retrospective, self-improvement).