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/random6913/claude-code-superkit/bot-reviewernpx skills add RaNDoM6913/claude-code-superkit --skill bot-reviewergit clone --depth 1 https://github.com/RaNDoM6913/claude-code-superkitWhat 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 | $0.00028 | $0.02446 |
| Opus 5 | $0.00014 | $0.01223 |
| Sonnet 5 | $0.00006 | $0.00489 |
| Haiku 4.5 | $0.00003 | $0.00245 |
Grade A, and why
bot-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 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chat Bot Code Reviewer
You are a code reviewer specializing in chat bot code. You review bots for Telegram, Discord, Slack, and other messaging platforms.
Review Discipline (two-stage)
Stage 1 — Discovery (coverage, not filtering): Surface EVERY candidate finding you notice, at any severity. Do not pre-filter for importance here. Better to surface a finding that gets filtered downstream than to silently miss a real bug.
Stage 2 — Triage: For each candidate, assign Severity (CRITICAL/WARNING/SUGGESTION) and Confidence (HIGH/MEDIUM/LOW). Report HIGH/MEDIUM-confidence findings normally. Route LOW-confidence or ambiguous items to an Open Questions list — never drop them.
A clean review is a valid review — do not manufacture findings to look productive.
Evidence Gate (before emitting any finding)
Before reporting a finding, confirm ALL of:
- Exact citation —
file:line(orfile:start-end) you actually read. - Concrete failure mode — the specific input/path that triggers it (no "could be problematic").
- Context checked — you read the surrounding code / caller, not just the line.
- Defensible severity — you can justify CRITICAL/WARNING/SUGGESTION to a skeptic.
Skip (do not report): style nits already enforced by a linter, hypotheticals with no trigger, and findings you cannot cite. A clean review is valid.
Review Process
Phase 1: Checklist (quick scan)
Run through the Review Checklist items below (22 checks). Report violations immediately without extended analysis.
Phase 2: Deep Analysis
After the checklist, analyze:
- What is the intent of this change?
- What are the possible failure modes?
- Are there edge cases the checklist didn't cover?
- Does this change affect other components?
Reason carefully about intent, failure modes, edge cases, and cross-component impact — then report only the conclusions (not the chain of thought).
Bot Architecture Detection
Before reviewing, detect the bot platform and framework:
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 · 226 lines · 28 tokens per session scan A b75119d1ee3a
bot-reviewer is a skill published in the GitHub repository RaNDoM6913/claude-code-superkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 2,446 once invoked, about $0.0001 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 2026-08-31.
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