HumanLayer is a software system that runs coding agents on a team’s machines and coordinates their tasks, sessions, plans, and reviews through desktop and web apps. Its Turborepo monorepo contains the user interfaces, host daemon, API, command-line tools, synchronization services, and agent plugins. The catalogue entries provide skills, plugins, instructions, and settings for its coding-agent workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add humanlayer/humanlayer --skill create-prdgit clone --depth 1 https://github.com/humanlayer/humanlayerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/humanlayer/humanlayer/create-prd)<a href="https://agentmods.dev/skills/humanlayer/humanlayer/create-prd"><img src="https://agentmods.dev/badge/skills/humanlayer/humanlayer/create-prd/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/humanlayer/humanlayer/create-prd"><img src="https://agentmods.dev/badge/skills/humanlayer/humanlayer/create-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.02683 |
| Opus 5.5 | $0.00006 | $0.01073 |
| Sonnet 5.5 | $0.00003 | $0.00537 |
| Haiku 4.5 | $0.00002 | $0.00268 |
Grade A, and why
create-prd scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 15d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PRD Phase
You are creating a Product Requirements Document (PRD): the artifact that turns a raw idea, ticket, or pain point into a product spec the team can design and build from. It answers WHAT we're building and WHY - the user experience, functionality, and behavior. Leave technical implementation to the downstream TDD.
You run the PRD as a guided conversation. You settle the foundation - the problem and what success looks like - then grill the solution one question at a time, re-working the document after every answer so it always reads as a coherent spec - never a transcript of Q&A.
How the conversation works (read this before you start)
Exactly one question per message. End every message with a single question - never a second question, a stacked follow-up, or an "and also...". Offering 2-3 options to choose between is still one question; stacking multiple independent decisions into one message is not allowed. Walk down the solution tree one decision at a time: present the decision with its options, tradeoffs, and your recommendation, then stop and wait. If several things feel open, ask only the one that unblocks the rest - the others come after the answer. Never ask for a vague "any feedback?".
Run each decision as an interview loop; patch the doc only once the decision is resolved. Ask your one question, then work back and forth until it's settled. The user won't always answer outright - they may push back, think out loud, or ask a clarifying question of their own ("well, how would it work if quality finding = 'passing'?"). That's still part of the conversation, not a decision: answer it, keep the discussion going, and leave the document alone. A single user message is not by itself a cue to edit - patching mid-discussion churns the spec and derails the back-and-forth. Only once the decision is actually resolved do you flush it to the doc and move on to the next question.
When you flush a resolved decision, re-work the relevant section rather than appending to it. Fold the decision in: rewrite prose, redraw a mockup or diagram, reorder or remove earlier content as needed. A single decision often revises parts of the spec that have already started to emerge. Capture each decision in whatever form conveys it best - a mockup, diagram, or sketch - reaching for one when the decision calls for it, regardless of whether the question itself used one.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 15d ago First seen · 157 lines · 16 tokens per session scan A 98b38b8ce889
create-prd is a skill published in the GitHub repository humanlayer/humanlayer (12,815 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 2,683 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-23.
create-prd compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| create-prdhumanlayer/humanlayer | Skill | 13k | yesterday | Apache-2.0 | A | 16 | Claude Code, Codex |
| agent-fsdesplega-ai/agent-fs | Skill | 24 | yesterday | MIT | B | 569 | Claude Code |
| ai-agent-evaluation-benchmarkingsickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 31 | Claude Code |
| otto-pr-review-loopomnigent-ai/omnigent | Skill | 11k | yesterday | Apache-2.0 | A | 17 | Claude Code, Codex |
| deploy-docker-composeomnigent-ai/omnigent | Skill | 11k | yesterday | Apache-2.0 | A | 84 | Claude Code, Codex |
| feature-designomnigent-ai/omnigent | Skill | 11k | yesterday | Apache-2.0 | A | 24 | Claude Code, Codex |
| security-auditomnigent-ai/omnigent | Skill | 11k | yesterday | Apache-2.0 | A | 64 | Claude Code, Codex |