pr-env-reviewer

pr-env-reviewer is a skill for Claude Code, Codex from AndrewNgGirl/SkillLens. It costs 34 tokens per session (62 once invoked), scanned A, original, MIT.

A focused reviewer for environment-related changes in a pull request, which is a proposed code change awaiting review.

In plain words
What is it for?
Use it when a review pipeline needs environment findings from a code diff.
Why use it?
It helps identify environment and configuration problems during the review of the change.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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 skills/andrewnggirl/skilllens/env
Any agent
npx skills add AndrewNgGirl/SkillLens --skill env
Clone the repo
git clone --depth 1 https://github.com/AndrewNgGirl/SkillLens

Made for: Claude Code, Codex.

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 pr-env-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/andrewnggirl/skilllens/env.svg)](https://agentmods.dev/skills/andrewnggirl/skilllens/env)
Your own site
<a href="https://agentmods.dev/skills/andrewnggirl/skilllens/env"><img src="https://agentmods.dev/badge/skills/andrewnggirl/skilllens/env.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 62 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 5.1 $0.00034 $0.00062
Opus 5 $0.00017 $0.00031
Sonnet 5 $0.00007 $0.00012
Haiku 4.5 $0.00003 $0.00006

Measured 6d ago against content hash 69ee1aff79fe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

pr-env-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 6d 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/skill-scorer/examples/mega-pipeline/agents/env/SKILL.md · 8 lines

What it actually says

Env reviewer

Specialist for env concerns in PR review.

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. 6d ago First seen · 8 lines · 34 tokens per session scan A 69ee1aff79fe

Subscribe to this mod's changes

pr-env-reviewer is a skill published in the GitHub repository AndrewNgGirl/SkillLens (75 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 62 once invoked, about $0.0002 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 2026-08-30.