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 skills add 0xrafasec/ai-workflow --skill adrgit clone --depth 1 https://github.com/0xrafasec/ai-workflowWrote 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/0xrafasec/ai-workflow/adr)<a href="https://agentmods.dev/skills/0xrafasec/ai-workflow/adr"><img src="https://agentmods.dev/badge/skills/0xrafasec/ai-workflow/adr/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/0xrafasec/ai-workflow/adr"><img src="https://agentmods.dev/badge/skills/0xrafasec/ai-workflow/adr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00075 | $0.00652 |
| Opus 5.5 | $0.00030 | $0.00261 |
| Sonnet 5.5 | $0.00015 | $0.00130 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
adr 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 1mo 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create an Architecture Decision Record. Argument: $ARGUMENTS
Context
ADRs capture a single decision — the context, options considered, and the choice made. They're lightweight and accumulate over time. Each ADR is a separate numbered file.
Context Gathering
- Check
docs/adr/for existing ADRs — determine the next number. If no ADRs exist, start at0001. - Read recent ADRs (last 2-3) to match the project's style and voice.
- If the decision relates to architecture, read
docs/ARCHITECTURE.mdfor context.
Interview
Use AskUserQuestion to extract the decision. Keep it focused — an ADR is one decision, not a design doc.
- What's the decision? — What are you deciding? What triggered this decision?
- Context — What constraints, requirements, or pressures led to this? What's the current state?
- Options considered — What alternatives did you evaluate? What are the tradeoffs of each?
- Decision — What did you choose and why? What was the deciding factor?
- Consequences — What changes as a result? What are the known downsides you're accepting?
If the decision is straightforward (user already knows what they want and why), keep the interview to 1-2 questions to fill in gaps.
Write
Write to docs/adr/NNNN-<slug>.md:
# ADR-NNNN: [Title]
**Status:** Proposed | Accepted | Deprecated | Superseded by [ADR-XXXX]
**Date:** [date]
**Deciders:** [who was involved]
## Context
[What is the issue? What forces are at play? What constraints exist?]
## Decision
[What was decided. State it clearly in one sentence, then elaborate if needed.]
## Options Considered
### Option A: [Name]
- **Pros:** [benefits]
- **Cons:** [drawbacks]
### Option B: [Name]
- **Pros:** [benefits]
- **Cons:** [drawbacks]
### Option C: [Name] (if applicable)
- **Pros:** [benefits]
- **Cons:** [drawbacks]
## Consequences
### Positive
- [What improves]
### Negative
- [What gets harder or what risks are accepted]
### Neutral
- [What changes without clear positive/negative valence]
## Related
- [Links to related ADRs, specs, issues, or documents]
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.
- 1mo ago First seen · 82 lines · 75 tokens per session scan A 45b020c125c0
adr is a skill published in the GitHub repository 0xrafasec/ai-workflow (9 stars, last pushed 1mo ago), licensed MIT. It adds 75 tokens to every session and 652 once invoked, about $0.0003 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.
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