third-lens-review

third-lens-review is a skill for Claude Code from Paretofilm/superpowers-gstack. It costs 54 tokens per session (2,188 once invoked), scanned A, original, no licence file.

A review step that sends a completed code change to a third, independent AI model after reviews by Claude and Codex. It then combines the findings and checks the patched result for hidden problems.

In plain words
What is it for?
Use it to review high-risk code changes, compare independent findings, and produce an adversarial summary before shipping.
Why use it?
Different AI models can miss different issues. This adds another independent check for important changes involving architecture, security, runtime behavior, or interfaces between systems.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the superpowers-gstack plugin — 19 skills, 3 hooks shipped together

Good fit Use it to review high-risk code changes, compare independent findings, and produce an adversarial summary before shipping.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/paretofilm/superpowers-gstack/third-lens-review
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.

Any agent
npx skills add Paretofilm/superpowers-gstack --skill third-lens-review
Clone the repo
git clone --depth 1 https://github.com/Paretofilm/superpowers-gstack

Made for: Claude Code.

Or install superpowers-gstack, the plugin that ships this one along with the rest of its 19 skills, 3 hooks.

Wrote 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.

agentmods badge for third-lens-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/paretofilm/superpowers-gstack/third-lens-review/github.svg)](https://agentmods.dev/skills/paretofilm/superpowers-gstack/third-lens-review)
Your own site
<a href="https://agentmods.dev/skills/paretofilm/superpowers-gstack/third-lens-review"><img src="https://agentmods.dev/badge/skills/paretofilm/superpowers-gstack/third-lens-review/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.

agentmods 80×15 button for third-lens-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/paretofilm/superpowers-gstack/third-lens-review"><img src="https://agentmods.dev/badge/skills/paretofilm/superpowers-gstack/third-lens-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,188 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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 5.1 $0.00054 $0.02188
Opus 5.5 $0.00022 $0.00875
Sonnet 5.5 $0.00011 $0.00438
Haiku 4.5 $0.00005 $0.00219

Measured 1mo ago against content hash 5665a3750531, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

third-lens-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 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.

skills/third-lens-review/SKILL.md · 117 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 1mo ago Changed · +2 lines 5665a3750531
  2. 1mo ago First seen · 115 lines · 54 tokens per session scan A a24bb4c132d6

Subscribe to this mod's changes

third-lens-review is a skill published in the GitHub repository Paretofilm/superpowers-gstack (2 stars, last pushed yesterday), with no licence file. It adds 54 tokens to every session and 2,188 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

great_cto

Use when the CTO describes a feature, task, or project goal. Orchestrates the full SDLC pipeline automatically based on project type.

avelikiy/great_cto · 32 tokens

opportunity-solution-tree

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to customer opportunities, possible solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when the team is unclear what to build next, when multiple opportunities compete, or before writing a…

avelikiy/great_cto · 71 tokens

skeptical-triage

Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of 4 extra LLM turns.

avelikiy/great_cto · 49 tokens

anti-patterns

Catalogue of known SDLC anti-patterns that greatcto agents must actively reject when reviewing architecture, plans, code, or post-mortems. Used by architect (pre-impl), pm (planning), senior-dev (impl), l3-support (post-incident).

avelikiy/great_cto · 59 tokens

well-architected

6-pillar architecture review framework. Adapted from AWS Well-Architected for use by greatcto's architect agent on every non-nano ARCH document. Forces explicit answers across operational excellence, security, reliability, performance, cost, and sustainability — not just feature design.

avelikiy/great_cto · 60 tokens

product-economics

Does this product make money at a price someone will pay? Forces contribution margin, a price with a stated basis, and a bottom-up market size — each number labelled measured / assumed / unknown, so a guess can never be read as a calculation.

avelikiy/great_cto · 55 tokens