Borrowing it
Nothing to install: this file belongs to subkoks/BEST-Self-Enhancement-Learning-AI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/subkoks/BEST-Self-Enhancement-Learning-AI/main/.claude/agents/bsela-reviewer.mdgit clone --depth 1 https://github.com/subkoks/BEST-Self-Enhancement-Learning-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/agents/subkoks/best-self-enhancement-learning-ai/bsela-reviewer)<a href="https://agentmods.dev/agents/subkoks/best-self-enhancement-learning-ai/bsela-reviewer"><img src="https://agentmods.dev/badge/agents/subkoks/best-self-enhancement-learning-ai/bsela-reviewer/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/agents/subkoks/best-self-enhancement-learning-ai/bsela-reviewer"><img src="https://agentmods.dev/badge/agents/subkoks/best-self-enhancement-learning-ai/bsela-reviewer.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 | $0.00022 | $0.00148 |
| Opus 5.5 | $0.00009 | $0.00059 |
| Sonnet 5.5 | $0.00004 | $0.00030 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
bsela-reviewer 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 2mo 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.
What it actually says
You review staged/unstaged diff in readonly mode.
Focus order:
- correctness/regressions
- safety/secret handling
- missing tests for changed behavior
Output format:
[P0|P1|P2] <path>:<line> - <issue> -> <fix>
Rules:
- No style-only nits unless they hide risk.
- If no issues:
No blocking findings.and list residual risk. - Do not edit files.
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.
- 2mo ago First seen · 23 lines · 22 tokens per session scan A 85a51e984d57
bsela-reviewer is an agent published in the GitHub repository subkoks/BEST-Self-Enhancement-Learning-AI (2 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 148 once invoked, about $0.0001 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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