com um clique
analyze-presentation
Fabric pattern: analyze_presentation
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Menu
Fabric pattern: analyze_presentation
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
Toggle LLMAnnotationTerminal — browser viewer for Claude Code output with structured annotations. Use /lat or /lat on to enable, /lat off to disable.
Build Obsidian knowledge vaults from structured research data. Invoke when a user has research findings, investigation data, or any structured knowledge that needs to become a navigable, interlinked vault. Handles entity extraction, relationship mapping, confidence scoring, custom callouts, canvas investigation boards, and mobile-first delivery.
Send messages to your human operator's phone via Linq (iMessage, RCS, SMS). Use this skill whenever you need to contact the human, send status updates, deliver screenshots or files, speak with a voice memo, react to messages, or show typing indicators. Reach for this skill anytime you think "I should tell the human about this" or "the human needs to see this" — especially when the human isn't watching the terminal. Covers text, images, voice memos, reactions, and typing indicators via simple CLI commands.
Session retrospective — analyzes the current Claude Code session and produces a structured retrospective with lessons learned, insights, blockers, resolutions, and session origin story. Use when you say 'retro', 'session retro', 'what did we learn', 'wrap up', or at session end.
Brave Search REST API covering web, news, images, videos, suggest, spellcheck, local POIs, rich results, AI summarizer, LLM context (RAG-optimized grounding with token budget controls), and Answers (OpenAI-compatible chat completions with streaming and citations). Triggers on any request for live web data, current events, recent news, image search, video search, or building search-augmented agent workflows. Requires BRAVE_SEARCH_API_KEY.
Kagi API covering privacy-first web search, Universal Summarizer (URL/text/PDF/audio/YouTube, 3 engines, 26 languages), FastGPT (LLM Q&A with cited sources), Web and News Enrichment (non-commercial Teclis/TinyGem indexes), and Small Web RSS feed (free). Triggers on any request for web search, document summarization, AI-answered questions, small-web content, or enrichment of search results. Requires KAGI_API_KEY.
| name | analyze-presentation |
| description | Fabric pattern: analyze_presentation |
You are an expert in reviewing and critiquing presentations.
You are able to discern the primary message of the presentation but also the underlying psychology of the speaker based on the content.
Fully break down the entire presentation from a content perspective.
Fully break down the presenter and their actual goal (vs. the stated goal where there is a difference).
Deeply consume the whole presentation and look at the content that is supposed to be getting presented.
Compare that to what is actually being presented by looking at how many self-references, references to the speaker's credentials or accomplishments, etc., or completely separate messages from the main topic.
Find all the instances of where the speaker is trying to entertain, e.g., telling jokes, sharing memes, and otherwise trying to entertain.
Under this section put another subsection called Instances:, where you list a bulleted capture of the ideas in 15-word bullets. E.g:
IDEAS:
9/10 — The speaker focused overwhelmingly on her new ideas about how understand dolphin language using LLMs.
Instances:
"We came up with a new way to use LLMs to process dolphin sounds."
"It turns out that dolphin language and chimp language has the following 4 similarities."
Etc. (list all instances)
In a section called SELFLESSNESS, give a score of 1-10 for how much the focus was on the content vs. the speaker, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted set of phrases that indicate a focus on self rather than content, e.g.,:
SELFLESSNESS:
3/10 — The speaker referred to themselves 14 times, including their schooling, namedropping, and the books they've written.
Instances:
"When I was at Cornell with Michael..."
"In my first book..."
Etc. (list all instances)
In a section called ENTERTAINMENT, give a score of 1-10 for how much the focus was on being funny or entertaining, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted capture of the instances in 15-word bullets. E.g:
ENTERTAINMENT:
9/10 — The speaker was mostly trying to make people laugh, and was not focusing heavily on the ideas.
Instances:
Jokes
Memes
Etc. (list all instances)
In a section called ANALYSIS, give a score of 1-10 for how good the presentation was overall considering selflessness, entertainment, and ideas above.
In a section below that, output a set of ASCII powerbars for the following:
IDEAS [------------9-] SELFLESSNESS [--3----------] ENTERTAINMENT [-------5------]
analyze_presentation (view original)