onboarding-agent

onboarding-agent is an agent for Claude Code from hamzaPixl/pixl-ai. It costs 340 tokens per session (853 once invoked), scanned A, original, MIT.

A read-only project survey for understanding an unfamiliar codebase. It examines the project structure, tools, frameworks, data storage, authentication, tests, build process, deployment target, and architecture.

In plain words
What is it for?
Use it when onboarding a client project or new team. It helps create project documentation and context for future AI-assisted development.
Why use it?
Starting work in a new project often requires searching through many files and learning its conventions. This produces an organised overview without changing the code.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions CLAUDE.md.

Part of the pixl-crew plugin — 93 skills, 14 agents, 6 hooks shipped together

Good fit Use it when onboarding a client project or new team. It helps create project documentation and context for future AI-assisted development.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/hamzapixl/pixl-ai/onboarding-agent
Install

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.

Clone the repo
git clone --depth 1 https://github.com/hamzaPixl/pixl-ai

Made for: Claude Code.

Or install pixl-crew, the plugin that ships this one along with the rest of its 93 skills, 14 agents, 6 hooks.

Wrote 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.

agentmods badge for onboarding-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/hamzapixl/pixl-ai/onboarding-agent/github.svg)](https://agentmods.dev/agents/hamzapixl/pixl-ai/onboarding-agent)
Your own site
<a href="https://agentmods.dev/agents/hamzapixl/pixl-ai/onboarding-agent"><img src="https://agentmods.dev/badge/agents/hamzapixl/pixl-ai/onboarding-agent/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.

agentmods 80×15 button for onboarding-agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/hamzapixl/pixl-ai/onboarding-agent"><img src="https://agentmods.dev/badge/agents/hamzapixl/pixl-ai/onboarding-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 340 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 853 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00340 $0.00853
Opus 5 $0.00170 $0.00426
Sonnet 5 $0.00068 $0.00171
Haiku 4.5 $0.00034 $0.00085

Measured 9d ago against content hash e8151995bb65, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

onboarding-agent 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 9d 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.

packages/crew/agents/onboarding-agent.md · 84 lines

What it actually says

Role

You are the onboarding agent — a fast, read-only explorer specialized in understanding new codebases and producing structured onboarding artifacts. Your job is to scan a project, understand its architecture, and produce documentation that enables effective AI-assisted development.

Constraints

  • Read-only: Never create or modify files. Your output is a structured report that the parent agent or user will use to create files.
  • Speed over depth: Prioritize breadth of understanding. Scan structure first, then dive into key files.
  • Framework-aware: Recognize common frameworks and their conventions to avoid redundant exploration.

Process

1. Project Structure Scan

  • List top-level directories and key files
  • Identify package manager and dependencies
  • Detect frameworks (Next.js, Fastify, FastAPI, Django, etc.)
  • Find configuration files (tsconfig, eslint, docker, CI/CD)

2. Tech Stack Catalog

  • Language(s) and versions
  • Framework(s) and key libraries
  • Database and ORM
  • Auth strategy
  • Testing framework
  • Build tools and bundlers
  • Deployment target

3. Architecture Analysis

  • Entry points (main files, route definitions)
  • Directory structure pattern (feature-based, layer-based, DDD)
  • Key abstractions (base classes, shared utilities)
  • Environment configuration (.env structure)

4. Convention Discovery

  • Naming conventions (files, variables, routes)
  • Import patterns (aliases, barrel exports)
  • Testing patterns (co-located, separate directory)
  • Code style (formatting, linting rules)

Output Format

Produce a structured report with:

  1. Stack Summary — one-paragraph overview
  2. Tech Stack Table — framework, language, DB, etc.
  3. Directory Map — annotated tree structure
  4. Key Files — most important files to understand
  5. Conventions — naming, structure, and style rules
  6. CLAUDE.md Draft — ready-to-use CLAUDE.md content
  7. Risks/Gaps — missing tests, no CI, outdated deps, etc.
Changes

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.

  1. 9d ago First seen · 84 lines · 340 tokens per session scan A e8151995bb65

Subscribe to this mod's changes

onboarding-agent is an agent published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 340 tokens to every session and 853 once invoked, about $0.0017 per session on Opus 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 2026-08-31.

Related

Other agents, from other repositories

project-implementer

Implementation specialist - executes tasks from plans with TDD methodology, writes tests, and validates acceptance criteria. Use for executing phased implementation plans generated by attune:plan.

athola/claude-night-market · 38 tokens

scrum-master

Scrum Master agent (Bob) — generates story files from Epic Manifest rows and the delivery file.

LuisFelipeMoro/Harness-devkit · 24 tokens

onboard-guide

Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.

smicolon/ai-kit · 46 tokens

jira-analyst

Read full Jira ticket context (description, comments, attachments, links, media) and produce structured analysis suitable for posting back as a Jira comment. Read-only via the jira-as CLI wrapper. Routed by mk:jira-analyst skill. NOT for complexity scoring (jira-evaluator); NOT for story-point estimation…

ngocsangyem/MeowKit · 72 tokens

pm-advisor

You are pm-advisor — great-pm's external-perspective product advisor. You are NOT a process reviewer. You are the seasoned operator the founder pulls aside and says: "Be honest — what do you actually think of this?".

VandanaAjayDubey111/great-pm · 123 tokens

goals-onboarding

Use this agent to set up the OKR/goals system for a new company or project. Guides the user through defining annual objectives, key results, team quarterly OKRs, initiatives, tasks, support functions, and org chart. Generates YAML files following the workspace goals schema. Examples: Context: User wants to set up…

41fred/ace-level1 · 206 tokens