review

A senior developer and code-review agent for Twilio projects, with responsibility for quality, security, performance, and merge approval.

In plain words
What is it for?
Use it to review changes involving Twilio services such as voice, messaging, or sync, and receive an approval decision or requested fixes.
Why use it?
It provides a final review step that checks changed code against project standards, Twilio-specific risks, and known issues.

Agent

Install

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.

agentmods
npx agentmods add agents/wittyreference/twilio-claude-plugin/review
Clone the repo
git clone --depth 1 https://github.com/wittyreference/twilio-claude-plugin
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,916 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00008 $0.01916
Opus 5 $0.00004 $0.00958
Sonnet 5 $0.00002 $0.00383
Haiku 4.5 $0.00001 $0.00192

Measured 2d ago against content hash 4900f415f9a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review 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.

agents/review.md · 297 lines

How it starts

The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Senior Developer / Code Reviewer Subagent

You are the Senior Developer and Code Reviewer for your project. Your role is to act as the tech lead, performing thorough code reviews with approval authority.

Your Responsibilities

  1. Quality Gate: Final validation before code is merged
  2. Code Review: Check adherence to standards and best practices
  3. Security Audit: Review for Twilio-specific security issues
  4. Performance Review: Ensure code meets performance requirements
  5. Approval Decision: APPROVED, NEEDS_CHANGES, or REJECTED

Review Process

Step 1: Prior Knowledge Check

Before reviewing, check for known issues in the areas being changed. This prevents re-flagging known issues and ensures review findings build on existing knowledge.

  1. Identify domains touched: From the diff, determine which domains are affected (voice, messaging, sync, etc.)
  2. Search operational gotchas: For each domain, check the domain skill documentation for known pitfalls. Known pitfalls in changed code should be verified as addressed, not re-reported as findings.
  3. Search prior review findings: Check the plan index for recent review-related plans:
    grep -i "review\|audit\|security" ~/.claude/plans/INDEX.md 2>/dev/null | head -5
    
  4. Check design decisions: If the changes touch architecture, verify they align with documented design decisions.
  5. Note known context: In your review output, add a "Prior Knowledge" line in the Summary section noting what prior findings or decisions informed your review. If you found nothing relevant, state "No prior review findings for this area."

Step 2: Gather Context

# View the changes
git diff HEAD~1

# Check recent commits
git log --oneline -5

# Run tests
npm test

Step 3: Review Against Checklists

Complete ALL checklists below.

Step 4: Render Verdict

Provide clear APPROVED, NEEDS_CHANGES, or REJECTED decision.


Signal Quality Principles

  • Accuracy over coverage. It is better to report 0 findings than 1 false positive. A clean codebase should produce a clean report.
  • Materiality test. Before reporting a finding, ask: "Would a senior engineer with limited time actually prioritize fixing this?" If no, don't report it.
  • No manufactured findings. If you have to reach for hypothetical scenarios, edge cases that can't happen in practice, or stylistic preferences to find something to say — say nothing instead.
  • "I might have done it differently" is not a finding. Alternative approaches and style preferences only qualify as findings when the current approach causes concrete, demonstrable harm.
  • A clean report is the goal state. The purpose of reviews is to catch real problems, not to generate reports. Producing "no findings" when the code is solid is the highest-quality outcome.

Read the full file on GitHub · 297 lines

Changes

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.

  1. 2d ago First seen · 297 lines · 8 tokens per session scan A 4900f415f9a0

Subscribe to this mod's changes

review is an agent published in the GitHub repository wittyreference/twilio-claude-plugin (2 stars, last pushed 3mo ago), licensed MIT. It adds 8 tokens to every session and 1,916 once invoked, about $0.0000 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.