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/itsribbz/godspeed/auroranpx skills add itsribbZ/Godspeed --skill auroragit clone --depth 1 https://github.com/itsribbZ/GodspeedWrote 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/itsribbz/godspeed/aurora)<a href="https://agentmods.dev/skills/itsribbz/godspeed/aurora"><img src="https://agentmods.dev/badge/skills/itsribbz/godspeed/aurora.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 | $0.00068 | $0.01351 |
| Opus 5 | $0.00034 | $0.00675 |
| Sonnet 5 | $0.00014 | $0.00270 |
| Haiku 4.5 | $0.00007 | $0.00135 |
Grade A, and why
aurora 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 5d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Aurora — The Dawn Tuner
Aurora was the Roman goddess of the dawn — the one who arrives before everyone else is awake. In Homer, she runs before the user wakes up, mining last night's Brain telemetry and proposing weight adjustments for the next day.
Role
Aurora is a sleep-time agent (L6). She reads Brain's decisions.jsonl and computes:
- Tier distribution (S0-S5 counts + percentages)
- Model recommendation distribution (haiku / sonnet / opus)
- Guardrail fire rates (which guardrails fire how often)
- Uncertainty escalation rate (% of prompts where classifier was unsure)
- Correction-detected rate (% of prompts flagged as corrections)
- Average classifier confidence
From those stats, Aurora generates proposals for routing_manifest.toml weight adjustments. She never auto-applies. Every proposal lands in a dated JSON file for the user's review.
Proposal Rules (current ruleset)
| Signal | Threshold | Proposal |
|---|---|---|
uncertainty_escalated firing > 40% |
Medium severity | Raise fail_open_tier from S3 to S4 OR raise confidence threshold |
correction_detected > 5% |
High severity | Bump correction_keywords weight in [signals] |
| Any guardrail firing > 20% | Low severity | Review threshold — possibly over-sensitive |
| Any guardrail firing 0× over 100+ decisions | Low severity | Verify still needed or retire |
avg_confidence < 0.5 |
Medium severity | Review signal weights; may need recalibration |
Each proposal in the output JSON contains:
id— unique identifierrationale— why Aurora proposes itrecommendation— what to changeseverity—high/medium/lowevidence— the raw numbers the proposal is based on
Input
- Primary:
~/.claude/telemetry/brain/decisions.jsonl(written bybrain_advisor.shUserPromptSubmit hook) - Secondary:
~/.claude/telemetry/brain/advisor_calls.jsonl(when it exists — written bybrain advise) - Reference:
Toke/automations/brain/routing_manifest.toml(current weights)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 113 lines · 68 tokens per session scan A 85fdb785b06c
aurora is a skill published in the GitHub repository itsribbZ/Godspeed (1 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 1,351 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 2026-08-31.
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