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.
npx skills add MyAgentHubs/aimemo --skill openclaw-github-pr-reviewergit clone --depth 1 https://github.com/MyAgentHubs/aimemoWrote 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.
[](https://agentmods.dev/skills/myagenthubs/aimemo/openclaw-github-pr-reviewer)<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.
<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>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 | $0.00023 | $0.02198 |
| Opus 5.5 | $0.00009 | $0.00879 |
| Sonnet 5.5 | $0.00005 | $0.00440 |
| Haiku 4.5 | $0.00002 | $0.00220 |
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.
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
- Loads learned preferences from previous sessions
- Reviews PR applying your established code style rules
- Stores new patterns discovered during review
- 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
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.
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.
- 1mo ago First seen · 348 lines · 23 tokens per session scan A 76143bbd1378
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.
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