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/RaNDoM6913/claude-code-superkitWrote 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/random6913/claude-code-superkit/bot-reviewer)<a href="https://agentmods.dev/agents/random6913/claude-code-superkit/bot-reviewer"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/bot-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/random6913/claude-code-superkit/bot-reviewer"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/bot-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 | $0.00015 | $0.03334 |
| Opus 5.5 | $0.00006 | $0.01334 |
| Sonnet 5.5 | $0.00003 | $0.00667 |
| Haiku 4.5 | $0.00002 | $0.00333 |
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 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telegram Bot Code Reviewer — SocialApp
You are a code reviewer specializing in Telegram bot code for the SocialApp project. You review both bot_moderator and bot_support bots.
Phase 0: Load Project Context
Read if exists:
CLAUDE.mdorAGENTS.md— project conventionsdocs/architecture/— relevant architecture docs for the task at hand
Use this context to:
- Know project-specific conventions and patterns
- Identify documented rules to check with HIGH confidence
- Understand the tech stack and framework in use
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 (sections 1-22). 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?
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 · 265 lines · 15 tokens per session scan A c61bd7db4e22
bot-reviewer is an agent published in the GitHub repository RaNDoM6913/claude-code-superkit (3 stars, last pushed 5d ago), licensed MIT. It adds 15 tokens to every session and 3,334 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 2026-09-03.
Other agents, from other repositories
fastapi-reviewer
Reviews FastAPI applications for async correctness, dependency injection, Pydantic schemas, security, OpenAPI quality, testing, and production readiness.
spring-boot-reviewer
Reviews Spring Boot codebases against all spring-boot skills for correctness, best practices, and Spring Boot 4 compatibility. Use when reviewing Spring Boot projects, validating implementations, or user mentions "review my Spring Boot code", "check Spring best practices", "Spring Boot review", "validate Spring…
changes-review
Changes review agent that verifies plan compliance, code quality, and goal achievement in a single pass. Returns structured JSON findings.
spec-review
Spec review agent that verifies alignment with user requirements and challenges dangerous assumptions. Returns structured JSON findings.
Vitruvius
Architecture reviewer. Evaluates system design decisions, architectural patterns, scalability, technical debt, and technology choices at the macro level. Use before committing to a system design, when something feels structurally wrong, or after a major sprint to audit what accumulated. Reports honesty ledger on…
Lyra
Writer/builder instrument. Takes a complete spec, returns a diff or built artifact. Use for schema migrations, adapter ports, dashboard patches, vault note synthesis, and any code edit with bounded scope. Reports honesty ledger on completion.