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 detect-thoughtsgit 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/detect-thoughts)<a href="https://agentmods.dev/skills/hmbown/wizards-of-the-ghosts/detect-thoughts"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/detect-thoughts/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/detect-thoughts"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/detect-thoughts.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 | $0.00079 | $0.00715 |
| Opus 5 | $0.00039 | $0.00358 |
| Sonnet 5 | $0.00016 | $0.00143 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
detect-thoughts 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Detect Thoughts
Surface the likely intent, priorities, and concerns behind a communication.
What This Skill Does
In D&D, Detect Thoughts lets you read surface thoughts and probe deeper. The real-world version is intent analysis: figuring out what someone is trying to accomplish based on what they said, how they said it, and what they chose not to say. This is the analytical complement to Insight (which reads subtext intuitively) — Detect Thoughts is more structured and systematic. In this grimoire, Detect Thoughts is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Detect Thoughts (spell).
When To Use
- You have a message, brief, or request and need to systematically extract the sender's priorities, concerns, and unstated goals.
- A requirements document or feature request needs to be decoded: what do they actually need vs. what they asked for?
- You want to prepare for a negotiation or conversation by mapping the other party's likely positions and concerns.
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.
- Read the communication and identify explicit statements of intent, priority, and concern.
- Analyze word choice, emphasis, and structure for implicit signals about what matters most.
- Map the gap between stated and likely intent: where do they diverge?
- Deliver the intent analysis with confidence levels and a recommendation for how to respond to the real priorities.
- Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.
Deliverables
- An intent analysis: stated goals, implicit priorities, and likely concerns ranked by importance.
- A gap analysis: where stated intent and likely real intent diverge, with evidence.
- A response recommendation that addresses real priorities, not just stated ones.
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 · 67 lines · 79 tokens per session scan A 1f20d1b89452
detect-thoughts 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 79 tokens to every session and 715 once invoked, about $0.0004 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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