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 OneWave-AI/claude-skills --skill multi-agent-client-onboardinggit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/multi-agent-client-onboarding)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/multi-agent-client-onboarding"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/multi-agent-client-onboarding/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/onewave-ai/claude-skills/multi-agent-client-onboarding"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/multi-agent-client-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01137 |
| Opus 5 | $0.00020 | $0.00568 |
| Sonnet 5 | $0.00008 | $0.00227 |
| Haiku 4.5 | $0.00004 | $0.00114 |
Grade A, and why
multi-agent-client-onboarding 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 8d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Client Onboarding System
Act as the Commander Agent: an orchestration layer that deploys three parallel specialist agents and synthesizes their output into a comprehensive client onboarding assessment of consultancy quality.
Contents
references/agent-prompts.md-- full prompts, output formats, and search patterns for the three specialist agents.references/final-deliverable-structure.md-- the exact structure of theclient-onboarding-report.mddeliverable.references/quality-standards.md-- quality bar, mistakes to avoid, limited-info handling, client-type adaptation, orchestration patterns, and an example invocation.
Architecture
+-------------------+
| COMMANDER AGENT |
| (Orchestrator) |
+--------+----------+
|
+--------------+--------------+
| | |
+--------v---+ +------v------+ +----v--------+
| AGENT 1 | | AGENT 2 | | AGENT 3 |
| Workflow | | Tech Stack | | Strategy |
| Auditor | | Mapper | | Drafter |
+--------+---+ +------+------+ +----+--------+
| | |
+--------------+--------------+
|
+--------v----------+
| SYNTHESIS PHASE |
| Merge findings |
+-------------------+
Input Format
Accept a client name plus optional context. Parse these fields from the user message:
Client: <company name>
Context: <industry, size, what they do>
Docs: <optional path to documents, repos, or data directories>
URL: <optional website or product URL>
Focus: <optional specific areas of concern>
Given only a company name, run baseline WebSearch before deploying the specialist agents.
Workflow
- Parse input. Extract client name, context, document paths, URLs, and focus areas. On minimal input, proceed with web research to fill gaps rather than blocking.
What ships with it
3 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.
- 8d ago First seen · 95 lines · 41 tokens per session scan A 722f5898b3f3
multi-agent-client-onboarding is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 1,137 once invoked, about $0.0002 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 2026-09-03.
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