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 foresightgit 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/foresight)<a href="https://agentmods.dev/skills/hmbown/wizards-of-the-ghosts/foresight"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/foresight/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/foresight"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/foresight.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 | $0.00181 | $0.01099 |
| Opus 5 | $0.00090 | $0.00549 |
| Sonnet 5 | $0.00036 | $0.00220 |
| Haiku 4.5 | $0.00018 | $0.00110 |
Grade A, and why
foresight 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foresight
Estimate likely outcomes before committing to a plan, change, or launch.
What This Skill Does
Foresight produces bounded forecasts with explicit uncertainty to guide decisions. It is NOT:
- Preflight checks: Verifying prerequisites before executing a known action (disk space, backups, connection strings). Those are safety gates, not forecasts.
- Diagnosis/Debugging: Finding what's broken right now (null pointers, deprecated APIs). Those are root-cause analyses, not predictions.
- Monitoring: Watching real-time metrics or alerting on thresholds. Those are observability tasks, not forward-looking estimates.
- Reconnaissance: Gathering facts about competitors or systems. Intelligence gathering feeds foresight but isn't foresight itself. Key distinction: If the user wants to know "what will likely happen if we choose X," use Foresight. If they want to know "is it safe to run X now," "what's broken," or "what are they doing," use a different spell. In this grimoire, Foresight is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Foresight (spell).
When To Use
- Activate this spell when the user asks for a forward-looking, probability-weighted forecast to inform a decision. Look for:
- Explicit choice between options ("should we X or Y?", "migrate vs stay", "build vs buy")
- Time-bounded outcome requests ("over the next 12 months", "by Q3", "18-month trajectory")
- Risk/uncertainty language ("risk-weighted", "confidence level", "probability", "best case/worst case", "weal or woe")
- Decision frameworks with explicit unknowns ("what would change your recommendation?", "decisive unknowns")
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.
- Scope the decision: Restate the choice, the time horizon, and what success/failure looks like.
- Map the paths: List the strongest upside and downside scenarios for each option.
- Estimate from evidence: Assign likelihoods based on current data, not vibes. State your assumptions explicitly.
- Return the forecast: Deliver (a) a recommendation with confidence level, (b) a short risk matrix, and (c) the decisive unknowns that would change the call.
- Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.
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 · 77 lines · 181 tokens per session scan A a2689d563801
foresight 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 181 tokens to every session and 1,099 once invoked, about $0.0009 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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