Agent skill

PonytailCoding Agents

Ask an agent for a date picker and you can get a dependency, a wrapper component, a stylesheet and a conversation about time zones, when the browser has had `<input type="date">` for years. Ponytail is a single skill aimed at that habit: it pushes the agent towards the smallest thing that works, and towards not writing anything when the platform already provides it. What makes it worth a look rather than a joke is that the maintainers measured it — twelve real tasks on a real repository, with and without the skill — and published the method alongside the numbers, including a note that an earlier, more flattering figure was the per-task ceiling rather than the average.

Addy Osmani's Agent SkillsCoding Agents

Left alone, a coding agent starts writing code the moment you finish the sentence. This is a set of skills that puts the usual engineering order back: nine commands cover the stages from working out what to build to shipping it, and the skills behind them attach on their own when the work calls for one — designing an interface pulls in the interface skill, touching the front end pulls in that one. Notably the automatic mode does not remove the checks, only the person stepping between tasks: each task is still test-driven, committed on its own, and paused on failure. It is Markdown, so it installs into around seventy agents through the open skills command.

HumanizerTools & Integrations

The problem with asking a model to make its own writing sound less like a model is that it has no list of what gives it away. Humanizer supplies one: thirty-five patterns from the checklist Wikipedia's editors maintain for spotting AI-written articles. It drafts a rewrite without treating the original structure as fixed, then checks that draft against the same patterns and against the original claims before going again, and it shows the intermediate pass and its own critique rather than only the result. It does not invent: names, numbers, dates and citations must come from the source. Pointed at a file it changes prose only, leaving code, data and link targets alone.

Scientific Agent SkillsTools & Integrations

An agent can already call any Python library, but it will use a specialist bioinformatics package the way someone reads the docs for the first time — plausibly, and wrong in the ways that matter. This supplies the missing half: over 160 skills that carry the curated usage and worked examples for specific scientific tools, plus access to a hundred or so public databases, across genomics, chemistry, drug discovery, proteomics, clinical research, imaging, physics and geospatial work. It installs as one plugin or skill by skill. Read the scope notes before relying on it, though — the clinical and healthcare skills are written for research and retrospective validation, and say plainly that they are not for patient-specific decisions.

Diagram DesignTools & Integrations

Asking an agent for a diagram usually returns rounded boxes and arrows that look nothing like the document they are going into, so the diagram gets dropped. This skill gives the agent a vocabulary instead: thirty-nine named layouts — architecture, sequence, swimlane, quadrant, Sankey, fishbone, Wardley map, story map and more — each shipped in light, dark and full-editorial variants as one HTML file with inline SVG. No build step, no JavaScript, no external images: open the file in a browser or drop it into a page. It can also read your site to pick up the brand, and redraw an existing draw.io or Mermaid source at a chosen size and level of detail.

Planning with FilesMemory & Context

A long task fails in a particular way: the agent had a plan, the context was cleared or compacted, and what comes back is an agent confidently finishing a different job. This skill moves the plan out of the conversation and onto disk — one file for the plan, one for what has been found, one for what is done — and puts them back in front of the agent on every turn. Because the plan is a file, it outlives a clear, a crash and a compaction, and you can read it yourself while the run is going. An optional gate stops the agent declaring completion until the plan says so. The maintainers publish blind A/B results, which is more than most skills offer.

DistillyTools & Integrations

When the person who knew why the system is like that leaves, the documentation they wrote turns out to be the small half of what they knew. Distilly is an attempt at the other half: you give it their messages, documents, interviews or public writing, and it produces a profile of the observable pattern — how they decided things, what they insisted on, how they said it — packaged as a skill an agent can load. The maintainers are careful about what it claims, and so should you be: the output is grounded in the material you supplied and does not claim to be the person. The obvious caution is consent, since the material it works from is usually someone else's.

skillsTools & Integrations

Over a hundred skill directories of Google's own written guidance, installed selectively with `npx skills add google/skills`. The bulk sits under `skills/cloud` — GKE, BigQuery, Agent Platform, the six Well-Architected pillars — while `skills/ads` and `skills/analytics` cover the Google Ads API, the Mobile Ads and IMA SDKs and the two Google Analytics APIs. Depth is uneven: `skills/cloud/gke-*` accounts for twenty-nine directories on its own, Cloud Run and Firebase get one each, and the README labels the repository as under active development. A stack on neither Google Cloud nor Google's ads and analytics products gets nothing here, and app-side coverage stops at the Mobile Ads SDK — Android, Flutter, Dart, Genkit and ADK skills are separate repositories the README only links to.