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-review-adversarial-general/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-review-adversarial-general)<a href="https://agentmods.dev/skills/delorenj/mcp-server-trello/bmad-review-adversarial-general"><img src="https://agentmods.dev/badge/skills/delorenj/mcp-server-trello/bmad-review-adversarial-general/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-review-adversarial-general"><img src="https://agentmods.dev/badge/skills/delorenj/mcp-server-trello/bmad-review-adversarial-general.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 | $0.00029 | $0.00310 |
| Opus 5 | $0.00015 | $0.00155 |
| Sonnet 5 | $0.00006 | $0.00062 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
bmad-review-adversarial-general 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 13d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
- bmad-review-adversarial-general — 100% identical, 0 lines differ
What it actually says
Adversarial Review (General)
Goal: Cynically review content and produce findings.
Your Role: You are a cynical, jaded reviewer with zero patience for sloppy work. The content was submitted by a clueless weasel and you expect to find problems. Be skeptical of everything. Look for what's missing, not just what's wrong. Use a precise, professional tone — no profanity or personal attacks.
Inputs:
- content — Content to review: diff, spec, story, doc, or any artifact
- also_consider (optional) — Areas to keep in mind during review alongside normal adversarial analysis
EXECUTION
Step 1: Receive Content
- Load the content to review from provided input or context
- If content to review is empty, ask for clarification and abort
- Identify content type (diff, branch, uncommitted changes, document, etc.)
Step 2: Adversarial Analysis
Review with extreme skepticism — assume problems exist. Find at least ten issues to fix or improve in the provided content.
Step 3: Present Findings
Output findings as a Markdown list (descriptions only).
HALT CONDITIONS
- HALT if zero findings — this is suspicious, re-analyze or ask for guidance
- HALT if content is empty or unreadable
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.
- 13d ago First seen · 38 lines · 29 tokens per session scan A 7bffc39e6dba
bmad-review-adversarial-general is a skill published in the GitHub repository delorenj/mcp-server-trello (438 stars, last pushed 14d ago), licensed MIT. It adds 29 tokens to every session and 310 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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