Moltis is a persistent personal agent server written in Rust that runs on hardware controlled by its user. It provides an AI agent with sandboxed command execution, model-provider connections, memory, voice, scheduling, messaging integrations, browser automation, and MCP tools. Its catalogue add-ons extend the agent’s workflows and available tools.
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 moltis-org/moltis --skill github-code-reviewgit clone --depth 1 https://github.com/moltis-org/moltisWrote 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/moltis-org/moltis/github-code-review)<a href="https://agentmods.dev/skills/moltis-org/moltis/github-code-review"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/github-code-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.
<a href="https://agentmods.dev/skills/moltis-org/moltis/github-code-review"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/github-code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 22 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 31 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 32 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 144 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 157 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 198 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 224 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 229 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 254 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 259 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 357 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 361 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 419 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 425 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 196 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 227 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 257 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 423 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- low Supply Chain · line 142 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- low Supply Chain · line 155 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- low Supply Chain · line 196 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
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 | $0.00045 | $0.03663 |
| Opus 5.5 | $0.00018 | $0.01465 |
| Sonnet 5.5 | $0.00009 | $0.00733 |
| Haiku 4.5 | $0.00005 | $0.00366 |
Grade C, and why
github-code-review scanned grade C with 2 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
elif grep -q "github.com" ~/.git-credentials 2>/dev/null; then Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: Review code changes by analyzing git diffs, leaving inline comments on PRs, and performing thorough pre-push review. Works with gh CLI or falls back to git + GitHub REST API via curl. Copies of this mod
8 near-identical copies found in the catalogue:
- github-code-review — 98% identical, 27 lines differ
- github-code-review — 98% identical, 29 lines differ
- github-code-review — 97% identical, 27 lines differ
- github-code-review — 97% identical, 27 lines differ
- github-code-review — 94% identical, 28 lines differ
- github-code-review — 92% identical, 30 lines differ
- github-code-review — 91% identical, 31 lines differ
- github-code-review — 89% identical, 42 lines differ
How it starts
The opening of the file, as written. The whole thing — 480 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Code Review
Perform code reviews on local changes before pushing, or review open PRs on GitHub. Most of this skill uses plain git — the gh/curl split only matters for PR-level interactions.
Prerequisites
- Authenticated with GitHub (see
github-authskill) - Inside a git repository
Setup (for PR interactions)
if command -v gh &>/dev/null && gh auth status &>/dev/null; then
AUTH="gh"
else
AUTH="git"
if [ -z "$GITHUB_TOKEN" ]; then
if [ -f your environment ] && grep -q "^GITHUB_TOKEN=" your environment; then
GITHUB_TOKEN=$(grep "^GITHUB_TOKEN=" your environment | head -1 | cut -d= -f2 | tr -d '\n\r')
elif grep -q "github.com" ~/.git-credentials 2>/dev/null; then
GITHUB_TOKEN=$(grep "github.com" ~/.git-credentials 2>/dev/null | head -1 | sed 's|https://[^:]*:\([^@]*\)@.*|\1|')
fi
fi
fi
REMOTE_URL=$(git remote get-url origin)
OWNER_REPO=$(echo "$REMOTE_URL" | sed -E 's|.*github\.com[:/]||; s|\.git$||')
OWNER=$(echo "$OWNER_REPO" | cut -d/ -f1)
REPO=$(echo "$OWNER_REPO" | cut -d/ -f2)
1. Reviewing Local Changes (Pre-Push)
This is pure git — works everywhere, no API needed.
Get the Diff
# Staged changes (what would be committed)
git diff --staged
# All changes vs main (what a PR would contain)
git diff main...HEAD
# File names only
git diff main...HEAD --name-only
# Stat summary (insertions/deletions per file)
git diff main...HEAD --stat
Review Strategy
- Get the big picture first:
git diff main...HEAD --stat
git log main..HEAD --oneline
- Review file by file — use
read_fileon changed files for full context, and the diff to see what changed:
git diff main...HEAD -- src/auth/login.py
- Check for common issues:
# Debug statements, TODOs, console.logs left behind
git diff main...HEAD | grep -n "print(\|console\.log\|TODO\|FIXME\|HACK\|XXX\|debugger"
# Large files accidentally staged
git diff main...HEAD --stat | sort -t'|' -k2 -rn | head -10
# Secrets or credential patterns
git diff main...HEAD | grep -in "password\|secret\|api_key\|token.*=\|private_key"
# Merge conflict markers
git diff main...HEAD | grep -n "<<<<<<\|>>>>>>\|======="
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 · 480 lines · 45 tokens per session scan C 9b52522f849b
github-code-review is a skill published in the GitHub repository moltis-org/moltis (2,889 stars, last pushed 24d ago), licensed MIT. It adds 45 tokens to every session and 3,663 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 2 findings (reaches for credential files, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
openclaw-github-dedupe
Investigate a cluster of GitHub issues and PRs, determine canonical candidates, post duplicate/related status, preserve contributor credit, and execute cleanup actions. Supports autonomous mode for provided-link-only closeout, merge/fix follow-through, changelog, and post-merge issue/PR cleanup.
openclaw-pr-batch-sweep
Select, review, repair, validate, and land batches of up to 20 low-risk OpenClaw contributor pull requests using Vincent's maintainer preferences and bounded sub-agent lanes. Use for "next 20", broad contributor PR sweeps, merge-candidate mining, or continued PR-batch work where drafts, maintainer work, trivial…
simplicio-orient
Terminal-first execution — answer facts with the shell, never with the LLM. Use whenever a step needs a fact about the filesystem, git, processes, or system resources, or runs a build/test/lint/diff whose output would flood context. Substitutes deterministic shell/CLI calls for native LLM operations and clamps their…
simplicio-review
Deep, adversarial branch review — parallel subagents on separate rubrics (security/correctness, code-quality, and does-it-reproduce), spawned in one message, then deduped into one verdict. Runs for EVERY item, no TRIVIAL/SMALL shortcut — it is 3 of the 6 roles in simplicio-tasks' minimum-agent floor. Use before…
code-review
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use…
pr
Use when writing a PR body.