github-pr-reviewer-aimemo

github-pr-reviewer-aimemo is a skill for Claude Code, Codex from MyAgentHubs/aimemo. It costs 23 tokens per session (2,198 once invoked), scanned A, original, MIT.

A GitHub pull-request review process that remembers a developer's code-style preferences using persistent memory.

In plain words
What is it for?
Use it to review GitHub pull requests, record style patterns, and reuse feedback in later reviews.
Why use it?
It keeps review feedback consistent across sessions and applies previously learned preferences when checking new pull requests.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to review GitHub pull requests, record style patterns, and reuse feedback in later reviews.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/myagenthubs/aimemo/openclaw-github-pr-reviewer
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 MyAgentHubs/aimemo --skill openclaw-github-pr-reviewer
Clone the repo
git clone --depth 1 https://github.com/MyAgentHubs/aimemo

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 github-pr-reviewer-aimemo

README.md
[![agentmods](https://agentmods.dev/badge/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer/github.svg)](https://agentmods.dev/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer)
Your own site
<a href="https://agentmods.dev/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer"><img src="https://agentmods.dev/badge/skills/myagenthubs/aimemo/openclaw-github-pr-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.

agentmods 80×15 button for github-pr-reviewer-aimemo

Your own site · 80×15
<a href="https://agentmods.dev/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer"><img src="https://agentmods.dev/badge/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,198 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.02198
Opus 5.5 $0.00009 $0.00879
Sonnet 5.5 $0.00005 $0.00440
Haiku 4.5 $0.00002 $0.00220

Measured 1mo ago against content hash 76143bbd1378, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

github-pr-reviewer-aimemo 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.

examples/openclaw-github-pr-reviewer/SKILL.md · 348 lines

How it starts

The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub PR Reviewer with aimemo Memory

This skill reviews GitHub Pull Requests and learns your code style preferences over time using aimemo's persistent memory.

How It Works

  1. Loads learned preferences from previous sessions
  2. Reviews PR applying your established code style rules
  3. Stores new patterns discovered during review
  4. Remembers feedback you provide for future reviews

Memory Integration

CRITICAL: This skill uses aimemo for persistent memory. Always pass context: "github-pr-reviewer-aimemo" to all memory tool calls.

On Session Start

ALWAYS call memory_context FIRST before reviewing:
{
  "context": "github-pr-reviewer-aimemo"
}

This loads:

  • Code style preferences
  • Common patterns to watch for
  • Previous feedback and corrections
  • In-progress review tasks

During Review

Store discoveries immediately:

{
  "context": "github-pr-reviewer-aimemo",
  "entities": [{
    "name": "code-style-preferences",
    "entityType": "preferences",
    "observations": ["New pattern you discovered"]
  }]
}

On Session End

Write a journal entry:

{
  "context": "github-pr-reviewer-aimemo",
  "journal": "Reviewed PR #123. Updated: variable naming rules. Next: discuss error handling patterns with user."
}

Instructions

When the user asks you to review a GitHub PR:

Step 1: Load Memory (MANDATORY)

Before doing ANYTHING else, call:

memory_context({
  "context": "github-pr-reviewer-aimemo"
})

This gives you access to:

  • User's code style preferences
  • Previously identified anti-patterns
  • Ongoing review tasks
  • Past user feedback

Step 2: Fetch PR Details

Use GitHub API or ask user for PR link. Retrieve:

  • PR title and description
  • Changed files and diffs
  • Existing review comments
  • PR metadata (author, labels, etc.)

Step 3: Review Code

Apply learned preferences from memory:

Code Style:

  • Check naming conventions (snake_case, camelCase, etc.)
  • Verify indentation and formatting
  • Look for trailing commas, semicolons based on preferences

Read the full file on GitHub · 348 lines

Files

What ships with it

1 file 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.

  1. 1mo ago First seen · 348 lines · 23 tokens per session scan A 76143bbd1378

Subscribe to this mod's changes

github-pr-reviewer-aimemo is a skill published in the GitHub repository MyAgentHubs/aimemo (1 stars, last pushed 8mo ago), licensed MIT. It adds 23 tokens to every session and 2,198 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 2026-08-31.

Related

Other skills, from other repositories

prove

Per-surface verification loops for wenlan — daemon, cli, mcp, plugin, suite strength (mutation), behavior trace, weekly sweep. Routes to scripts; every check records evidence via attest. Deeper than the built-in verify skill — use prove for mutation audits, behavior tracing, and the weekly sweep; built-in /verify…

wenlan-app/wenlan · 74 tokens

slm-graph

Index and query a codebase as a structural graph — build the code graph, trace blast radius of a change, find callers/callees/inheritors, semantic code search by meaning, assemble PR review context, and detect what changed since last index. Use when the user asks how code connects, what breaks if X changes, what calls…

qualixar/superlocalmemory · 97 tokens

memtrace-style-fingerprint

Pull the codebase's empirical style norm from Memtrace and match it when writing or editing source code in an indexed repo. Use when choosing between competing idioms (ternary vs if-else, arrow vs function declaration, const vs let, await vs .then, early-return vs nested-return), matching naming case, or when the user…

syncable-dev/memtrace-public · 111 tokens

cartograph

Explore a codebase through Cartograph v2's native RocksDB code graph: intent-aware context, exact/BM25/hybrid search, callers/callees/impact, affected tests, live source, review, freshness, and bounded index administration.

adder-factory/cartograph · 0 tokens

memtrace-refactoring-guide

Build a phased, risk-scored refactoring plan from Memtrace complexity, dead-code, bridge, impact analysis, and Cortex decision-memory constraints. Use when the user wants to refactor source code, reduce complexity, clean technical debt, delete dead code, split large functions, extract modules, reorganize code, or…

syncable-dev/memtrace-public · 100 tokens

memtrace-code-review

Review GitHub pull requests with Memtrace's local graph-backed review engine. Use when the user asks to review a GitHub pull request, run Memtrace code review, post Memtrace review comments, create a PR with a review step, or publish local graph-backed review findings to GitHub. Prefer the reviewgithubpr MCP tool over…

syncable-dev/memtrace-public · 110 tokens