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-researchgit 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-research)<a href="https://agentmods.dev/skills/humanlayer/humanlayer/create-research"><img src="https://agentmods.dev/badge/skills/humanlayer/humanlayer/create-research/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-research"><img src="https://agentmods.dev/badge/skills/humanlayer/humanlayer/create-research.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 | $0.03719 |
| Opus 5.5 | $0.00006 | $0.01488 |
| Sonnet 5.5 | $0.00003 | $0.00744 |
| Haiku 4.5 | $0.00002 | $0.00372 |
Grade A, and why
create-research scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
sessionStore.fetch(sessionId) How it starts
The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Codebase
You are tasked with conducting comprehensive research across the codebase to answer user questions by spawning parallel sub-agents and synthesizing their findings.
CRITICAL: YOUR ONLY JOB IS TO DOCUMENT AND EXPLAIN THE CODEBASE AS IT EXISTS TODAY
- DO NOT suggest improvements or changes unless the user explicitly asks for them
- DO NOT perform root cause analysis unless the user explicitly asks for them
- DO NOT propose future enhancements unless the user explicitly asks for them
- DO NOT critique the implementation or identify problems
- DO NOT recommend refactoring, optimization, or architectural changes
- ONLY describe what exists, where it exists, how it works, and how components interact
- You are creating a technical map/documentation of the existing system
Initial Setup:
When this command is invoked, check the task artifact directory from your system prompt for documents like *research-questions*.md with ls -La (the directory may be a symlink - do NOT use regular ls or grep/glob tools). If you find one, read it and proceed with the contents as the research query.
If you see several, ask the user which one to proceed with before reading any of them.
If you do not know what the task artifact directory is from your system prompt, respond with:
I'm ready to research the codebase. Please provide your research question or area of interest, and I'll analyze it thoroughly by exploring relevant components and connections.
IMPORTANT: You may NEVER read ticket.md/task.md files or other files from the artifact directory which do not match the research-questions pattern above unless such a file is explicitly asked for by the user.
Then wait for the user's research query.
Steps to follow after receiving the research query:
- Read any directly mentioned files first:
- If the user mentions specific files (docs, JSON, research questions), read them FULLY first
- IMPORTANT: Use the Read tool WITHOUT limit/offset parameters to read entire files
- CRITICAL: Read these files yourself in the main context before spawning any sub-tasks
- DO NOT read ticket files - research must stay objective about the current codebase, not be influenced by what a ticket wants to build. The research questions already capture what needs to be investigated.
- This ensures you have full context before decomposing the research
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.
- today First seen · 300 lines · 16 tokens per session scan A 471c5659733a
create-research is a skill published in the GitHub repository humanlayer/humanlayer (11,717 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 3,719 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-23.
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