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 sanjay3290/ai-skills --skill julesgit clone --depth 1 https://github.com/sanjay3290/ai-skillsWrote 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/sanjay3290/ai-skills/jules)<a href="https://agentmods.dev/skills/sanjay3290/ai-skills/jules"><img src="https://agentmods.dev/badge/skills/sanjay3290/ai-skills/jules/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/sanjay3290/ai-skills/jules"><img src="https://agentmods.dev/badge/skills/sanjay3290/ai-skills/jules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 5 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 YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Privilege Escalation · line 40 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 Supply Chain · line 97 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.
- medium Data Exfiltration · line 97 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 171 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.
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 | $0.00095 | $0.02350 |
| Opus 5 | $0.00048 | $0.01175 |
| Sonnet 5 | $0.00019 | $0.00470 |
| Haiku 4.5 | $0.00010 | $0.00235 |
Grade A, and why
jules scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -H "x-goog-api-key: $JULES_API_KEY" \ How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jules Task Delegation
Delegate coding tasks to Google's Jules AI agent on GitHub repositories.
Environment Variables
| Variable | Required | Description |
|---|---|---|
JULES_API_KEY |
For API auth | API key from jules.google.com/settings |
Setup (Run Before First Command)
Two auth paths are available. Use Path 1 for interactive use, Path 2 for headless/agent use.
Path 1: CLI (Interactive)
1. Install CLI
which jules || npm install -g @google/jules
2. Check Auth
jules remote list --repo
If fails → tell user to run jules login (or --no-launch-browser for headless)
Path 2: API Key (Headless / Agent Use)
1. Get API Key
Get key from jules.google.com/settings (3-key limit per account).
2. Set Environment Variable
export JULES_API_KEY="your-api-key"
3. Verify
curl -s -H "x-goog-api-key: $JULES_API_KEY" \
"https://jules.googleapis.com/v1alpha/sessions?pageSize=1" | head -20
Common Setup (Both Paths)
Auto-Detect Repo
git remote get-url origin 2>/dev/null | sed -E 's#.*(github\.com)[/:]([^/]+/[^/.]+)(\.git)?#\2#'
If not GitHub or not in git repo → ask user for --repo owner/repo
Verify Repo Connected
Check repo is in jules remote list --repo. If not → direct to https://jules.google.com
Commands (CLI)
Create Tasks
jules new "Fix auth bug" # Auto-detected repo
jules new --repo owner/repo "Add unit tests" # Specific repo
jules new --repo owner/repo --parallel 3 "Implement X" # Parallel sessions
cat task.md | jules new --repo owner/repo # From stdin
Monitor
jules remote list --session # All sessions
jules remote list --repo # Connected repos
Retrieve Results
jules remote pull --session <id> # View diff
jules remote pull --session <id> --apply # Apply locally
jules teleport <id> # Clone + apply
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.
- 10d ago First seen · 302 lines · 95 tokens per session scan A 9dc57b3d508d
jules is a skill published in the GitHub repository sanjay3290/ai-skills (420 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 95 tokens to every session and 2,350 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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