What is pre-pr-review?

A pre-pull-request review workflow for a RedisVL branch. It compares the branch with main, reads changed code and its callers, chooses relevant review checks, fixes confirmed problems, and records what was reviewed for a human approver.

Use it before opening or marking a pull request ready, after substantial pushes, or when responding to automated or human review comments.

A pull request can contain issues that ordinary tests or a quick diff review miss. A written scope and evidence record helps the approver see which checks were performed and which were not.

How redis/redis-vl-python configures Claude Code and Codex

About the project

Redis Vector Library is a Python client for using Redis in AI applications, including vector search, embeddings, semantic caching, and memory for agents. It is used to build retrieval-augmented generation pipelines, recommendation systems, and other applications that search and manage AI-related data in Redis. The catalogue add-ons support its use through instructions and rules.

redis/redis-vl-python · 432 stars · on GitHub · docs.redisvl.com

Reuse

Borrowing it

Nothing to install: this file belongs to redis/redis-vl-python. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/redis/redis-vl-python/main/.agents/skills/pre-pr-review/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/redis/redis-vl-python

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/redis/redis-vl-python/pre-pr-review/github.svg)](https://agentmods.dev/skills/redis/redis-vl-python/pre-pr-review)

Your own site

<a href="https://agentmods.dev/skills/redis/redis-vl-python/pre-pr-review"><img src="https://agentmods.dev/badge/skills/redis/redis-vl-python/pre-pr-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/redis/redis-vl-python/pre-pr-review"><img src="https://agentmods.dev/badge/skills/redis/redis-vl-python/pre-pr-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,776 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 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.

Model	Per session	Once invoked
Fable 5.1	$0.00081	$0.01776
Opus 5.5	$0.00032	$0.00710
Sonnet 5.5	$0.00016	$0.00355
Haiku 4.5	$0.00008	$0.00178

Measured 3d ago against content hash a47f4dd44e02, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pre-pr-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 3d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/open_feedback.py, scripts/update_brief.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/skills/pre-pr-review/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pre-PR review

A human approves every merge to main. This review runs before they see the PR, so the problems it catches never reach them. Its output, the Reviewer Brief, gives them a head start: where to begin reading, where the change could still fail, and what nobody has checked.

The approver can only rely on the brief if it's accurate, so report only what you can tie to the code, and never claim a check you didn't run.

1. Scope the change

Diff the work against its merge base with main: git diff $(git merge-base origin/main HEAD) covers commits and uncommitted changes, and git status shows untracked files to read as well.
Read each changed file in full, not just the hunks. Bugs often sit in the unchanged lines a hunk depends on.
For every changed public function, method or class, read its callers and its sync or async twin (SearchIndex and AsyncSearchIndex, and so on). Drift between twins is one of this project's most common defects.
In a stack of PRs you may review the whole stack at once, but keep track of which PR introduced each line. Each PR gets its own brief.

2. Choose lenses

Run all six lenses by default. Each catches problems the others miss, and running all of them is the most thorough option.

A lens that finds nothing relevant in the diff has still done its job; say nothing about it beyond the footer. If you need to save tokens, the "Most useful when" column says where each lens pays off. Correctness always runs. The footer of the brief lists the lenses that ran, so the reviewer can see what was covered.

Lens	File	Most useful when
Correctness	`references/correctness.md`	Always
Security	`references/security.md`	The diff touches `redisvl/mcp/`, `redisvl/query/filter.py`, `redisvl/utils/token_escaper.py`, code that builds query strings or `SCAN` patterns, destructive methods (`delete`, `clear`, drop), `redisvl/redis/connection.py`, `.github/`, or dependencies
Design	`references/design.md`	Feature work, new or changed public API or MCP surface, work on deprecated APIs, new vectorizer, reranker or provider modules
Tests	`references/tests.md`	Tests are added or changed, or the change sits in an area CI can't exercise (cluster, live provider APIs)
Docs	`references/docs.md`	`docs/`, notebooks, docstrings or comments change, or public behaviour changes
Redis behaviour	`references/redis.md`	The diff changes how Redis commands or queries are built, relies on a server default, limit or reply shape, or states how Redis behaves

Read the full file on GitHub · 103 lines

Files

What ships with it

11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

3d ago Changed · +19 lines · +17 tokens per session a47f4dd44e02
10d ago First seen · 84 lines · 64 tokens per session scan A 6429d7d10509

Subscribe to this mod's changes

pre-pr-review is a skill published in the GitHub repository redis/redis-vl-python (432 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 1,776 once invoked, about $0.0003 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 2026-10-20.

Code review Commits Git and workflow LLM Python embedding large-language-models redis vector-database

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guardian

Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy; the ship recipe also executes PR delivery (create, CI watch, merge, cleanup) with Ask First on merge. Use when PR preparation, commit strategy, or gated PR delivery is needed.

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Change the user's own program, on their machine or through GitHub. Use when a request needs a change to the user's code (instrument tracing, wire the SDK, fix the agent behind a failing scenario, add a run parameter to a connected agent, version a hardcoded prompt) and not when the platform alone can do it (create a…

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redis-vl-python: Skill for Claude Code