Borrowing it
Nothing to install: this file belongs to DanceNitra/agora. 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/DanceNitra/agora/main/.claude/skills/open-world-forge/SKILL.mdgit clone --depth 1 https://github.com/DanceNitra/agoraWrote 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/dancenitra/agora/open-world-forge)<a href="https://agentmods.dev/skills/dancenitra/agora/open-world-forge"><img src="https://agentmods.dev/badge/skills/dancenitra/agora/open-world-forge/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/dancenitra/agora/open-world-forge"><img src="https://agentmods.dev/badge/skills/dancenitra/agora/open-world-forge.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 | $0.00189 | $0.02225 |
| Opus 5.5 | $0.00076 | $0.00890 |
| Sonnet 5.5 | $0.00038 | $0.00445 |
| Haiku 4.5 | $0.00019 | $0.00222 |
Grade A, and why
open-world-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 2mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open-World Forge — break the loop by anchoring on the books, not on ourselves
The owner's complaint that created this skill: "I want to go farther than the same loop about the same research." The old idea-forge read the brain's own substrate (ideation/inputs = canon, beliefs, recent ideas) and so it recycled — coherence of what's-already-in-view manufactures confidence and the generator converges on its own attractor.
We have measured this exact failure: a generator that weights its own prior output with super-linear self-trust locks a permanent fraction of its founding bias (Lab 75db49, the strange-loop attractor — 50% locked at p=2; needs a ≥3–5% external-evidence anchor to recover). The books say the same thing three ways — Kahneman (WYSIATI: confidence comes from the coherence of what's in view, not its completeness), Gazzaniga (the interpreter confabulates a coherent story for outputs it didn't derive), Johnson (the adjacent possible: the reachable frontier is only what current memory makes visible).
So the cure is structural, not stylistic: keep the external-evidence fraction HIGH and search for novelty/absence, not coherence. This skill is built so that every run must stand on material from outside our own canon.
The four rules that make it open-world (do not skip)
- External anchor every run. The primary substrate is the 36 books + cold vault domains, NOT our canon. The brain's self-knowledge is used for ONE thing only: to avoid repeating (the dedup/cold-domain set). Never let our own canon laws be the source of an idea.
- Rotate the draw (divergence by construction). Each run reads a different random subset of books and a different set of cold domains, so two runs can't converge on the same combination. (No
Math.randomneeded — vary by the date and what was drawn last, recorded in the note.) - Reward DISTANCE, not just feasibility. Score each idea on how far it sits from our current canon/recent-ideas. A safe, on-canon idea is the failure mode, not the goal. Surprise and "secrets" (Thiel) beat tidy coherence.
- Open targets. There are NO fixed targets (the old 4 — os/agora/mcp_memory/realworld — were part of the loop). Generate first, anywhere, civilization-scale allowed; tag applicability after.
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.
- 2mo ago First seen · 64 lines · 189 tokens per session scan A 706ae277fb12
open-world-forge is a skill published in the GitHub repository DanceNitra/agora (3 stars, last pushed 7d ago), licensed MIT. It adds 189 tokens to every session and 2,225 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-08-31.
open-world-forge compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| open-world-forgeDanceNitra/agora | Skill | 3 | 7d ago | MIT | A | 189 | Claude Code |
| Evaluationagentic-in/elephant-agent | Skill | 584 | 2mo ago | none | A | 25 | Claude Code, Codex |
| create-custom-graderNVIDIA/SkillEvaluator | Skill | 643 | yesterday | Apache-2.0 | A | 35 | Claude Code, Codex |
| api-callerNVIDIA/SkillEvaluator | Skill | 643 | yesterday | Apache-2.0 | A | 29 | Claude Code, Codex |
| calculatorNVIDIA/SkillEvaluator | Skill | 643 | yesterday | Apache-2.0 | A | 32 | Claude Code, Codex |
| text-analyzerNVIDIA/SkillEvaluator | Skill | 643 | yesterday | Apache-2.0 | A | 42 | Claude Code, Codex |
| company-braincaura-ai/caura | Skill | 549 | yesterday | Apache-2.0 | A | 108 | Claude Code |