Use biotech-pitch-deck-narrative for academic writing workflows that need structured investor-facing storytelling, explicit assumptions, and clear output boundaries.

Use figure reference checker for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.

Use grant budget justification for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.

Use poster layout planner for other workflows that need structured execution, explicit assumptions, and clear output boundaries.

Use lab budget forecaster for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.

Use preclinical pkpd analyst for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.

A comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival; use it when you need to model censored time-to-event outcomes, fit Cox/RSF/GB models or Survival SVMs, evaluate with C-index/Brier score, or handle competing risks.

Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.

> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)

Calculate literature growth velocity and acceleration to assess research.

IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities. Monitors cylinder pressure, calculates consumption rates, provides early warnings, and supports automated scheduling via cron.

Calculate medical date windows including gestational age, estimated delivery dates, and follow-up visit scheduling. Produces structured JSON output for clinical research and trial coordination workflows.

Local schedule management for adding events, tracking deadlines, generating reminders, and detecting time conflicts when users need offline scheduling with optional popup notifications.

StatsPAI is the agent-native Python package for causal inference and applied econometrics. One `import statspai as sp`, 900+ functions, covering the complete empirical research workflow.

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Utility commands — commit, compile, validate-bib, journal, context-status, deploy, learn. Replaces individual utility skills.

Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis

orchestrator

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Slash commands are frequently-used prompts defined as Markdown files that Claude executes during interactive sessions. Understanding command structure, frontmatter options, and dynamic features enable

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context-status

Final submission gate combining full verification, score enforcement, and submission checklist.

Systematic prompt engineering methods for AI-assisted academic research workf...

Core methods for empirical social science research including surveys and expe...

Set up RSS feeds and alerts to track new publications in your research area

AI-powered scientific writing workflow from outline to polished draft

Checklist-driven academic English polishing and Chinglish correction

Implement user skill change requests with optimization pattern evaluation

1. [Purpose](#purpose)

This skill provides an AI-driven workflow for analyzing SRT subtitle files and adding contextual reference cards below subtitle text blocks. Cards are intelligently selected based on content context a

This skill provides an AI-driven workflow for enhancing SRT subtitle files by comparing them with an original reference document (`origin.md`). The enhancement process corrects typos, standardizes pro

Status: Backlog

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Encrypt and decrypt files or streams using age — a simple, modern, and secure encryption tool with small explicit keys, passphrase support, SSH key support, post-quantum hybrid keys, and UNIX-style composability. No config options, no footguns.

Post notes, send encrypted messages, and interact with relays using the Nostr protocol.

Watch subreddits for people describing the problem you solve. Score their relevance. Draft a helpful reply for each match.

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Interactive conversational setup wizard for instar. Walks users through initial configuration and identity bootstrapping conversationally.

Automatically triggered when Tapestry is first launched on a new environment or lacks dependencies. Intelligently detects environment and installs Tapestry dependencies with user confirmation.

Simplify code while preserving behavior, public contracts, and side effects. Favor explicit code and local clarity over clever or compressed constructs.

Create atomic commits by staging the right files, analyzing the staged diff, composing a conventional commit message, and optionally pushing.

This skill should be run only when the user explicitly invokes it. Orchestrates end-to-end task implementation — understands the task, assesses complexity, implements directly or via a team of subagents for complex work, and always finishes with a code-polish pass.

**Company:** Series B Healthcare SaaS (80 people)

**Company context:** Series B healthcare SaaS, ~80 employees