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.
git clone --depth 1 https://github.com/ontorata/rataryWrote 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/rules/ontorata/ratary/agent-forge)<a href="https://agentmods.dev/rules/ontorata/ratary/agent-forge"><img src="https://agentmods.dev/badge/rules/ontorata/ratary/agent-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/rules/ontorata/ratary/agent-forge"><img src="https://agentmods.dev/badge/rules/ontorata/ratary/agent-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 | $0.00257 | $0.00257 |
| Opus 5.5 | $0.00103 | $0.00103 |
| Sonnet 5.5 | $0.00051 | $0.00051 |
| Haiku 4.5 | $0.00026 | $0.00026 |
Grade A, and why
agent-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.
What it actually says
Agent Forge (mandatory)
Before any design, code, test, or review work:
- Identify pipeline stage from docs-ai agent-forge workflows / product phase README under docs-ai · NOW.md
- Read and follow the matching skill in
.cursor/skills/forge-*/SKILL.md(skills remain in the Ratary Cursor workspace) - Run Recall at session start (
forge-recall) and Remember at session end (forge-remember) when MCP is available - Do not skip Intent → Isolate → Blueprint for non-trivial features (multi-file or structural)
- On failure, switch to
forge-diagnosebefore guessing fixes
Authority: docs-ai Knowledge OS > Agent Forge > ad-hoc prompts.
Legacy prompt IDs: search docs-ai designs/ / governance/ — do not duplicate long prompt text in chat.
Constitution: no agent runtime code in Ratary src/ — Forge is workflow law only.
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 · 20 lines · 257 tokens per session scan A 5789c75f77c6
agent-forge is a cursor rule published in the GitHub repository ontorata/ratary (1 stars, last pushed 2mo ago), licensed MIT. It adds 257 tokens to every session, about $0.0010 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.
Other cursor rules, from other repositories
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angular-20
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dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
config-validation-and-normalization
Config validation and normalization responsibilities (defineConfig normalizes, the orm section schema validates and resolves paths, the loader reports per-section diagnostics).
control-plane-descriptors
Control plane descriptor and instance implementation patterns.