Work with Synapdeck decks, notes, and note types from your AI client. Bundles the Synapdeck skills and a connection to the hosted Synapdeck MCP server.
0 on GitHubby SynapdeckApache-2.0updated 1 month ago
Not in a marketplace yet, so it loads for one session with --plugin-dir.
Plugin synapdeck in synapdeck/skills. Commands read from the repo's manifest — 1 month ago.
What it installs
Skills (2)
synapdeck-ad-hoc-scripts
Use when writing, debugging, or reviewing the Python ad hoc script attached to a Synapdeck note — the script that runs immediately before every card render to produce extra text fields, above all randomized parameters in math and science questions. Covers what scripts are for, when they run and deli
synapdeck-getting-started
Use when an AI agent needs to work with Synapdeck, the collaborative spaced-repetition flashcard platform — explains the core concepts and how to connect to Synapdeck's MCP server to browse decks, notes, and note types, and to create, update, or delete notes.
Statically analyze a local JS/Electron app you're authorized to study, with file+line evidence, and build an original reimplementation of what you find. Experimental. Phase 1: JS/Electron static analysis. Phase 2: native ELF/PE/Mach-O container inspection. Phase 3: .NET assembly metadata. Phase 4: EVM bytecode inventory. Phase 5: CUDA fatbin, cubin and PTX inventory. Parses, never executes. Dynamic analysis is a future phase, not yet implemented.
Drills Socratically, briefs cases, builds outlines, runs bar prep sessions tuned to your jurisdiction, grades IRAC practice, and plans the study schedule — without ever writing it for you.
Use when the user wants to know how a company gets its users, reverse engineer a competitor's growth or distribution, copy what a winning company does on each channel, or study a brand's content strategy (titles, thumbnails, covers, captions, graphics) on YouTube, TikTok, Instagram, X, LinkedIn or Reddit. Also for "how did X grow", "teardown of X's marketing", "what content works for X".
Study p-hacking in econometric designs: map researcher degrees of freedom, audit a specification search with a complete ledger and null-calibrated honest p-values, replay realistic search procedures, detect p-hacking in a literature, immunise an analysis, and benchmark whether an AI agent p-hacks. Research and teaching use only.
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