Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Helps choose a Proof of Life validation method suited to a hypothesis, its risks, and available resources. Aligns the probe with the actual learning goal rather than familiar tooling.
Covers expression-based manipulation, lazy query optimization, parallel execution, and streaming out-of-core processing. Supports pandas migration, Arrow interoperability, and optional GPU execution.
Supports overlap, nearest, merge, coverage, complement, and subtraction operations on genomic intervals. Handles BED, VCF, BAM, and GFF data with streaming and cloud-native workflows.
Locate company policies and explain them in plain language. Answer questions about benefits, travel, leave, expenses, remote work, and employee handbook rules.
Final quality pass before shipping. Fixes alignment, spacing, consistency, and detail issues that separate good from great.
Provides read-only sports prediction market intelligence without authentication, including live odds, prices, order books, and market search. Supports moneylines, spreads, totals, and player props. Excludes trading, news, historical match data, and actual results.
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, addi…
Promotes simple implementations by questioning unnecessary work and favoring standard libraries, native features, and fewer dependencies. Applies to coding, refactoring, fixes, reviews, and design, with lite, full, and ultra intensity levels.
Find the laziest solution that works: question whether the task needs to exist (YAGNI), prefer stdlib over custom code, one line over fifty. Use when user says "ponytail", "lazy mode", "simplest solution", "minimal", "yagni", or complains about over-engineering, bloat, or unnecessary dependencies.
Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.
Scans a whole repository for over-engineering and produces a ranked report of code to delete, simplify, or replace with standard library or native equivalents. Reports findings without applying fixes.
Harvest every ponytail: comment in the codebase into a debt ledger, so the deliberate shortcuts and deferrals ponytail leaves behind get tracked instead of rotting into "later means never". Use when the user says "ponytail debt", "/ponytail-debt", "what did ponytail defer", "list the shortcuts", "ponytail ledger", or "what did we mark to do later". One-shot report, changes nothing.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name