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 agentmods add skills/1a7432/loreweaver/rule-forgenpx skills add 1A7432/loreweaver --skill rule-forgegit clone --depth 1 https://github.com/1A7432/loreweaverWrote 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/1a7432/loreweaver/rule-forge)<a href="https://agentmods.dev/skills/1a7432/loreweaver/rule-forge"><img src="https://agentmods.dev/badge/skills/1a7432/loreweaver/rule-forge.svg" alt="Measured on agentmods" 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 | $0.00061 | $0.00536 |
| Opus 5 | $0.00030 | $0.00268 |
| Sonnet 5 | $0.00012 | $0.00107 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
Rule forge 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 4d 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.
What it actually says
Rule forge
You can author an entirely new TTRPG rule system, not just play the ones already installed
(coc7, dnd5e). When the keeper describes a rule system they want available -- its core
attributes/skills, how a check succeeds or fails, and any derived stats it needs -- call
generate_rulepack with a clear, self-contained description of it. Only call it when the keeper
is explicitly asking for a new rule system to be authored; never speculatively, and never in
response to ordinary play.
CoC 7e and D&D 5e are the reference packs: both are just rulepacks/<id>.yaml data files, so a
good description gives the same kind of detail their own sheets have.
A good description to pass along:
- names the system plainly (genre, tone, or the real TTRPG it's modeling, if any)
- lists its core attributes/skills and roughly what a starting character's values look like
- says how a check is resolved (roll-under, roll-over a target, dice-pool successes, ...)
- names any derived stats it needs (health, a damage bonus, per-attribute modifiers, ...) and, if you know it, roughly how each should be computed
What makes a good rule system: internally consistent math, sensible starting defaults for every
stat, and derived stats expressed as data wherever possible rather than reaching for a named
code computer. generate_rulepack will refuse (writing nothing) if the generated pack doesn't
parse, if its derived stats don't compile through the safe formula vocabulary, or if its id would
collide with a built-in system.
After generate_rulepack responds, tell the keeper plainly what was created (or why it wasn't, if
it failed) and note that the new system is now discoverable by its id/names.
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.
- 4d ago First seen · 43 lines · 61 tokens per session scan A 7543e5504cb6
Rule forge is a skill published in the GitHub repository 1A7432/loreweaver (49 stars, last pushed 3d ago), licensed MIT. It adds 61 tokens to every session and 536 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…