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/darkroomengineering/cc-settings/oraclenpx skills add darkroomengineering/cc-settings --skill oraclegit clone --depth 1 https://github.com/darkroomengineering/cc-settingsWhat 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 | $0.01977 |
| Opus 5 | $0.00030 | $0.00988 |
| Sonnet 5 | $0.00012 | $0.00395 |
| Haiku 4.5 | $0.00006 | $0.00198 |
Grade A, and why
oracle 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 2d 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oracle
Three-mode expert consultation: Advice for architectural guidance, Risks for premortem analysis, Compare for weighted approach evaluation.
Product-direction asks ("what should we build", positioning, market fit) belong to /strategist — a standing persona that explores the codebase for vision framing; this skill is a single-shot engineering consult.
Mode: Advice
How to Answer
- Understand the context - What is the user trying to achieve?
- Consider trade-offs - What are the pros/cons of different approaches?
- Recommend clearly - Give a definitive recommendation
- Explain why - Justify your recommendation
- Provide examples - Show, don't just tell
Response Format
## Recommendation
[Clear recommendation]
## Why
[Reasoning and trade-offs]
## Example
[Code or implementation example]
## Alternatives
[Other valid approaches and when to use them]
Remember
- Prioritize Darkroom conventions
- Store valuable insights as learnings
Mode: Risks
Analyze potential failure modes before they happen.
Purpose
Imagine the project has failed. What went wrong?
This technique surfaces risks that optimism bias might hide.
Analysis Framework
1. Technical Risks
- What could break?
- What dependencies might fail?
- What edge cases are unhandled?
- What performance issues might emerge?
2. Integration Risks
- How might this affect other parts of the system?
- What backwards compatibility issues exist?
- What migration challenges are there?
3. Operational Risks
- What could go wrong in production?
- What monitoring is missing?
- What recovery procedures are needed?
4. User Experience Risks
- How might users misuse this?
- What accessibility issues exist?
- What confusion might arise?
Output Format
## Premortem: [Feature/Change]
### High Risk
- [Critical failure mode]
→ Mitigation: [How to prevent]
### Medium Risk
- [Significant issue]
→ Mitigation: [How to address]
### Low Risk
- [Minor concern]
→ Mitigation: [Simple fix]
### Recommendations
1. [Priority action]
2. [Secondary action]
3. [Nice to have]
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.
- 2d ago First seen · 271 lines · 61 tokens per session scan A 80111763a5b8
oracle is a skill published in the GitHub repository darkroomengineering/cc-settings (42 stars, last pushed 4d ago), licensed MIT. It adds 61 tokens to every session and 1,977 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.
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