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 qGolem/orc --skill adrgit clone --depth 1 https://github.com/qGolem/orcWrote 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/qgolem/orc/adr)<a href="https://agentmods.dev/skills/qgolem/orc/adr"><img src="https://agentmods.dev/badge/skills/qgolem/orc/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/qgolem/orc/adr"><img src="https://agentmods.dev/badge/skills/qgolem/orc/adr.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 | $0.00009 | $0.02743 |
| Opus 5.5 | $0.00004 | $0.01097 |
| Sonnet 5.5 | $0.00002 | $0.00549 |
| Haiku 4.5 | $0.00001 | $0.00274 |
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 — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orc ADR
Research phase before implementation. Runs 4 parallel agents to find best practices, KOLs, and production code.
Avoid:
- Generic searches ("best practices TypeScript")
- Ignoring contradictory findings
- Creating ADRs without evidence
- Launching more than 4 agents (context limits)
Pattern
orc-adr (standalone skill, inherit)
│
├── [parallel] Web Search Agent (general-purpose)
├── [parallel] Twitter/X Agent (general-purpose)
├── [parallel] GitHub Agent (general-purpose)
└── [parallel] Docs Agent (general-purpose)
│
└── Synthesize → ADR(s)
Input
If $ARGUMENTS provided: Use as $TOPIC directly. If the topic looks like it references a plan phase (mentions a slug that exists in .claude/plans/), also load PLAN.md and STATE.md for richer context. Don't enforce a format — just work with what the user gives you.
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.
- 1mo ago First seen · 398 lines · 9 tokens per session scan A 30d07e5325e3
adr is a skill published in the GitHub repository qGolem/orc (5 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 2,743 once invoked, about $0.0000 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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