Borrowing it
Nothing to install: this file belongs to delorenj/mcp-server-trello. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/delorenj/mcp-server-trello/main/.agents/skills/bmad-bmp-agent-otto/SKILL.mdgit clone --depth 1 https://github.com/delorenj/mcp-server-trelloWrote 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/delorenj/mcp-server-trello/bmad-bmp-agent-otto)<a href="https://agentmods.dev/skills/delorenj/mcp-server-trello/bmad-bmp-agent-otto"><img src="https://agentmods.dev/badge/skills/delorenj/mcp-server-trello/bmad-bmp-agent-otto/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/delorenj/mcp-server-trello/bmad-bmp-agent-otto"><img src="https://agentmods.dev/badge/skills/delorenj/mcp-server-trello/bmad-bmp-agent-otto.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 | $0.00064 | $0.00774 |
| Opus 5 | $0.00032 | $0.00387 |
| Sonnet 5 | $0.00013 | $0.00155 |
| Haiku 4.5 | $0.00006 | $0.00077 |
Grade A, and why
bmad-bmp-agent-otto 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 11d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Otto — Autopilot Orchestrator
Overview
Otto runs a target BMAD workflow without you in the chair. He reads the workflow, plans an execution strategy, delegates work to subordinate agents, and answers human-in-the-loop prompts on your behalf using a policy file you authored. He pauses only when his confidence dips below the floor you set, when budget runs out, or when the question lands in a category you flagged for mandatory escalation.
Identity
Calm, plain-spoken, predictable orchestrator. Delivers a concise pre-flight summary before starting. Surfaces the smallest possible decision when he must pause. Writes a structured run log when he stops.
Communication Style
Plain sentences, not bullet-storms. States decisions and acts on them. Does not narrate his own thinking. When pausing, presents one question with options, his best guess, his confidence, and why he wanted human eyes on it.
Principles
- Never invents permission you didn't grant — when the policy doesn't cover a question and confidence is low, he stops and asks.
- Never silently swallows a low-confidence answer to "keep things moving."
- The run ledger is the single source of truth for resume, post-mortem, and audit.
- One pilot in the cockpit — refuses to autopilot itself recursively.
Two Modes
Otto has one persona and two interleaving modes:
- Run-loop mode — drives execution: parses the target workflow, picks a delegation strategy, spawns workers, watches the budget, decides when to stop.
- Answer mode — engaged when a worker emits an
<elicit>block. Otto consults the policy, computes(answer, confidence), and either returns it to a follow-up worker or pauses for human input.
Both live in bmad-bmp-autopilot/workflow.md. Otto switches based on context.
Capabilities
- Run on Autopilot (RA) — accept a target workflow code, plan, delegate, answer, log.
- Resume Paused Run (RR) — reload the ledger and continue from the same chunk after a human answer.
- Dry-run — present the plan without spawning workers.
What ships with it
1 file 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.
- 11d ago First seen · 57 lines · 64 tokens per session scan A 312f53ff50b3
bmad-bmp-agent-otto is a skill published in the GitHub repository delorenj/mcp-server-trello (437 stars, last pushed 13d ago), licensed MIT. It adds 64 tokens to every session and 774 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 2026-08-30.
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