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 Hmbown/Wizards-of-the-Ghosts --skill banegit clone --depth 1 https://github.com/Hmbown/Wizards-of-the-GhostsWrote 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/hmbown/wizards-of-the-ghosts/bane)<a href="https://agentmods.dev/skills/hmbown/wizards-of-the-ghosts/bane"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/bane/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/hmbown/wizards-of-the-ghosts/bane"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/bane.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 | $0.00070 | $0.00642 |
| Opus 5 | $0.00035 | $0.00321 |
| Sonnet 5 | $0.00014 | $0.00128 |
| Haiku 4.5 | $0.00007 | $0.00064 |
Grade A, and why
bane 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bane
Surface every weakness in a plan, system, or argument.
What This Skill Does
Bane curses targets, making them worse at everything they try. The real-world version is systematic weakness analysis: finding every crack, bad assumption, and failure mode in a plan, architecture, or argument. Unlike Vicious Mockery (which delivers the critique sharply), Bane is comprehensive and methodical — it maps the full attack surface. In this grimoire, Bane is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Bane (spell).
When To Use
- You need a thorough weakness analysis before committing to a plan, architecture, or strategy.
- Something feels fragile and you want to know exactly where it will break.
- You want a pre-mortem focused specifically on vulnerabilities rather than general risks.
Prerequisites
- No extra runtime dependencies beyond Hermes Agent and the normal toolset for this session.
Procedure
- Restate the target, the success condition, and any no-touch boundaries before taking action.
- Accept the target: the plan, system, argument, or design to analyze.
- Systematically probe each component, assumption, and dependency for weaknesses.
- Categorize weaknesses by severity and exploitability.
- Deliver a ranked vulnerability map with the most dangerous weaknesses first.
- Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.
Deliverables
- A ranked weakness map: every identified vulnerability sorted by severity.
- For each weakness, a brief note on how it could be exploited or how it would fail.
Pitfalls / Guardrails
- Keep the metaphor anchored to a real mechanism instead of drifting into lore.
- Bane finds weaknesses, it does not exploit them. The output is a diagnostic, not an attack plan.
- If the target has no significant weaknesses, say so. Forced negativity is as dishonest as forced positivity.
Verification
- Check that the result includes every deliverable promised above.
- Check that confirmed facts, assumptions, and inferences are visibly separated.
- Check that the metaphor still maps cleanly to a real operational mechanism.
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 · 66 lines · 70 tokens per session scan A c5ee35e417b8
bane is a skill published in the GitHub repository Hmbown/Wizards-of-the-Ghosts (107 stars, last pushed 5mo ago), licensed CC0-1.0. It adds 70 tokens to every session and 642 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 2026-09-03.
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