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/Intrafere/MOTO-Autonomous-ASIWrote 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/intrafere/moto-autonomous-asi/part-1-aggregator-tool-design-specifications)<a href="https://agentmods.dev/rules/intrafere/moto-autonomous-asi/part-1-aggregator-tool-design-specifications"><img src="https://agentmods.dev/badge/rules/intrafere/moto-autonomous-asi/part-1-aggregator-tool-design-specifications/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/intrafere/moto-autonomous-asi/part-1-aggregator-tool-design-specifications"><img src="https://agentmods.dev/badge/rules/intrafere/moto-autonomous-asi/part-1-aggregator-tool-design-specifications.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 | $0.03419 | $0.03419 |
| Opus 5 | $0.01709 | $0.01709 |
| Sonnet 5 | $0.00684 | $0.00684 |
| Haiku 4.5 | $0.00342 | $0.00342 |
Grade A, and why
part-1-aggregator-tool-design-specifications 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 11d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Description of entire rule: Main Architecture layout/design of the aggregator portion of the two-part aggregation-distillation LLM work flow.
OVERVIEW
Workflow for Aggregator Note
Submitters run in parallel; single validator reviews and updates the shared database sequentially. This ensures coherent Markov chain evolution and database alignment with user prompt.
AI Node Clusters and Validator Structure
Configurable 1-10 submitters + exactly 1 validator (default 3 submitters). Each submitter has its own model, context window, and max output tokens. First submitter labeled "Main Submitter" in UI.
Single Validator Constraint: Only one validator allowed — multiple validators would cause divergent database evolution, breaking coherent Markov chain alignment.
Validator accepts a submission if adding it makes the training database more useful toward finding solutions. Ordinary submissions aggressively pursue the strongest credible and genuinely novel solution to the user's exact objective, using the contribution form and claim-type rigor appropriate to the problem; mathematics, theorem discovery, proof, and formalization remain first-class whenever relevant, but non-mathematical work is not rejected merely for lacking mathematical form. Submissions must first prefer avenues that aggressively attack the user's WHOLE question as stated, no partial solutions. If the true answer is that the user's question is impossible or has no valid solution as stated, that counts as directly answering the whole question. If a whole-question attack is absolutely not possible in one superintelligence brainstorm, they may choose the next best necessary piece whose resolution would visibly advance the original question. Broader exploratory/background-heavy avenues are allowed only when clearly required for that whole-question route, and easy/practical/broad/interesting detours must lose to a more direct rigorous route to the full prompt. On a fresh cleared run the accepted-submissions database starts blank; on normal desktop runs it reloads persisted accepted submissions, stats, and top-level manual run activity from the active data root. Manual read-only results/events views hydrate persisted data without requiring Start; autonomous/mini-aggregators must not write the manual event log. Distributor updates all submitters after each acceptance.
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.
- 11d ago First seen · 133 lines · 3,419 tokens per session scan A 4a2eb7550c64
part-1-aggregator-tool-design-specifications is a cursor rule published in the GitHub repository Intrafere/MOTO-Autonomous-ASI (82 stars, last pushed 7d ago), licensed MIT. It adds 3,419 tokens to every session, about $0.0171 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.
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