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 hamzaPixl/pixl-ai --skill client-project-setupgit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote 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/hamzapixl/pixl-ai/client-project-setup)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/client-project-setup"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/client-project-setup/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/hamzapixl/pixl-ai/client-project-setup"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/client-project-setup.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 | $0.00058 | $0.00688 |
| Opus 5 | $0.00029 | $0.00344 |
| Sonnet 5 | $0.00012 | $0.00138 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
client-project-setup 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Client project onboarding pipeline: scan → catalog → generate CLAUDE.md → create context packet. Uses the onboarding-agent for exploration and produces ready-to-use project documentation.
Required References
Before starting, read references/methodology/client-onboarding.md for the onboarding checklist and CLAUDE.md template.
Step 1: Validate Input
- Confirm the project path exists and is a valid directory
- Check if a
CLAUDE.mdalready exists (offer to audit/improve instead of overwrite) - Check if
.claude/directory exists
Step 2: Codebase Exploration
Delegate to the onboarding-agent to perform a read-only scan of the project:
Launch onboarding-agent with prompt:
"Scan the project at {path}. Produce a complete onboarding report including:
stack summary, tech stack table, directory map, key files, conventions,
CLAUDE.md draft, and risks/gaps."
Step 3: Generate CLAUDE.md
Delegate to the /claude-md skill to produce the CLAUDE.md. Pass it the onboarding-agent's report as additional context. This avoids duplicating the CLAUDE.md generation logic.
If a CLAUDE.md already exists, use /claude-md in improve mode instead to audit and enhance it.
Step 4: Create Context Packet
Generate a .context/project-overview.md file with:
- Stack summary — for sharing with team members
- Architecture diagram (ASCII) — high-level component relationships
- Dependency map — key external services and integrations
- Risk register — technical debt, missing tests, security concerns
Step 5: Setup Recommendations
Based on the scan, recommend:
- Missing infrastructure:
- No CI/CD → suggest GitHub Actions
- No linting → suggest ESLint/Prettier or Ruff
- No testing → suggest test framework
- No Docker → suggest containerization
- pixl-crew integration:
- Which agents are most relevant for this project type
- Which skills to use first (e.g.,
/seo-auditfor websites,/ddd-patternfor backends)
- Quick wins:
- Easy improvements that can be made immediately
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.
- 9d ago First seen · 80 lines · 58 tokens per session scan A 82bc15118b46
client-project-setup is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 58 tokens to every session and 688 once invoked, about $0.0003 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.
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