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 agentmods add skills/abdullahmalik17/malikclaw/autonomous-dev-teamnpx skills add AbdullahMalik17/malikclaw --skill autonomous-dev-teamgit clone --depth 1 https://github.com/AbdullahMalik17/malikclawWrote 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/abdullahmalik17/malikclaw/autonomous-dev-team)<a href="https://agentmods.dev/skills/abdullahmalik17/malikclaw/autonomous-dev-team"><img src="https://agentmods.dev/badge/skills/abdullahmalik17/malikclaw/autonomous-dev-team.svg" alt="Measured on agentmods" 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 | $0.00021 | $0.00278 |
| Opus 5 | $0.00010 | $0.00139 |
| Sonnet 5 | $0.00004 | $0.00056 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
autonomous-dev-team 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 5d 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.
What it actually says
🤖 Autonomous Multi-Agent Team Skill
Use this skill when decomposing complex software goals into parallel, role-based workflows using MalikClaw's supervisor DAG engine.
Roles & Capabilities
- Architect (
architect): Decomposes high-level goals into modular DAG tasks (DependsOn). - Researcher (
researcher): Gathers specs, API docs, web content, and context. - Engineer (
engineer): Implements code, refactors functions, and writes unit tests. - QA & Auditor (
qa): Runs lints, performs security checks, and audits edge cases. - Communicator (
communicator): Formats technical summaries and user release notes.
Execution Flow
- Call
team_runwith the high-level goal:
{
"goal": "Build a secure OAuth 2.0 PKCE authentication module in Go"
}
- The orchestrator generates subtasks with explicit dependencies and executes ready tasks concurrently.
- Outputs are aggregated into a unified multi-agent consensus report.
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.
- 5d ago First seen · 31 lines · 21 tokens per session scan A 1285cad23d24
autonomous-dev-team is a skill published in the GitHub repository AbdullahMalik17/malikclaw (15 stars, last pushed 10d ago), licensed MIT. It adds 21 tokens to every session and 278 once invoked, about $0.0001 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 2026-08-30.
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