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/spencermarx/obsidian-aiWrote 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/commands/spencermarx/obsidian-ai/reviewers)<a href="https://agentmods.dev/commands/spencermarx/obsidian-ai/reviewers"><img src="https://agentmods.dev/badge/commands/spencermarx/obsidian-ai/reviewers/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/commands/spencermarx/obsidian-ai/reviewers"><img src="https://agentmods.dev/badge/commands/spencermarx/obsidian-ai/reviewers.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 | $0.00046 |
| Opus 5 | $0.00005 | $0.00023 |
| Sonnet 5 | $0.00002 | $0.00009 |
| Haiku 4.5 | $0.00001 | $0.00005 |
Grade A, and why
reviewers 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 10d 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.
This is a copy
100% identical to reviewers — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
OCR: Reviewers
This command is managed by Open Code Review.
Execute this command by reading and following: .ocr/commands/reviewers.md
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.
- 10d ago First seen · 10 lines · 9 tokens per session scan A 4b2351047e4c
reviewers is a command published in the GitHub repository spencermarx/obsidian-ai (48 stars, last pushed 4mo ago), licensed MIT. It adds 9 tokens to every session and 46 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to reviewers, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
plugin-audit
Run the full 8-phase plugin audit pipeline on a skill directory.
review
Run the local review gate before pushing.
review-feedback
Review a given code review markdown document, GitHub PR review, or inline feedback — corroborate each point against actual code, then implement valid changes.
translate-review-to-single-human
Translate a multi-reviewer code review into a single human-voice GitHub PR comment.
address
Address code review feedback — corroborate, validate, and implement changes from a review's final.md.
create-reviewer
Create a new custom reviewer from a natural language description.