Manus-style file-based planning that tracks complex work in task_plan.md, findings.md and progress.md — and restores context after /clear.
Designs statistically valid A/B tests end to end — hypothesis, sample size, guardrails, and result analysis.
Keeps task_plan.md, findings.md and progress.md on disk so multi-step work survives context loss and /clear.
A reference skill for designing, submitting, and retrieving protein experiments through the Adaptyv Foundry API and Python SDK.
Teaches Claude how to create, read, concatenate and optimize AnnData objects (.h5ad/.zarr) in the scverse ecosystem.
Guides Claude through classification, regression, clustering, forecasting, and anomaly detection on time series using the aeon toolkit.
Query 40+ bioinformatics databases such as UniProt, KEGG, ChEMBL and Reactome through one consistent Python interface.
Helps Claude write and debug Astropy code for units, coordinates, FITS I/O, tables, time scales, WCS and cosmology.
Turns Claude into a senior Angular architect for Angular 17+ standalone components, signals, NgRx, and RxJS patterns.
Scans a repository and produces an interactive knowledge graph of its architecture, components and relationships.
An interactive advisor that decides whether to scale, test, or kill a growth channel using unit economics, customer quality, and scalability.
Lists recent local Claude Code and OpenAI Codex conversations for a workspace with one read-only command.
A phase-based playbook for shipping pull requests that maintainers of third-party open-source repos actually merge.
Converts DOCX, PDF, and PPTX files into clean Markdown with eight automatic post-processing fixes.
A quality gate for Claude Code skills: audits your own or others' skills against official best practices and can even open an improvement PR.
A Git forensics skill that recovers lost commits, branches and stashes — and proves by content that cleanup won't drop any work.
Sets up, audits, and enforces internationalization in React/Next.js/Vue codebases — from framework config to replacing hard-coded strings and verifying locale key parity.
Turns vague requests into precise, testable specifications and structured prompts using EARS syntax.
Sets up and runs Promptfoo-based LLM evaluations, from config files to custom Python and LLM-rubric assertions.
Sets up an end-to-end QA process—test strategy, AAA-style test cases, execution tracking, P0–P4 bug triage, and quality-gate reporting—from ready-made templates and scripts.