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 agentmods add commands/leei1337/phantom-neural-cortex/reviewgit clone --depth 1 https://github.com/LEEI1337/phantom-neural-cortexWrote 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/commands/leei1337/phantom-neural-cortex/review)<a href="https://agentmods.dev/commands/leei1337/phantom-neural-cortex/review"><img src="https://agentmods.dev/badge/commands/leei1337/phantom-neural-cortex/review.svg" alt="Measured on agentmods" 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 | $0.00007 | $0.00182 |
| Opus 5 | $0.00003 | $0.00091 |
| Sonnet 5 | $0.00001 | $0.00036 |
| Haiku 4.5 | $0.00001 | $0.00018 |
Grade A, and why
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 5d 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.
What it actually says
Code Review Task
Please review the code with focus on:
1. Security
- Check for common vulnerabilities (SQL injection, XSS, CSRF, etc.)
- Validate input handling and sanitization
- Review authentication and authorization
- Check for exposed secrets or credentials
2. Performance
- Identify potential bottlenecks
- Check for unnecessary database queries (N+1 problems)
- Review memory usage and potential leaks
- Analyze algorithm complexity
3. Code Quality
- Follow SOLID principles
- Check for code duplication (DRY)
- Verify proper error handling
- Review naming conventions
- Check for proper comments and documentation
4. Best Practices
- Language-specific best practices
- Framework conventions
- Testing coverage
- Logging and monitoring
Please provide specific recommendations for improvements.
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.
- 5d ago First seen · 35 lines · 7 tokens per session scan A 7068570f7af0
review is a command published in the GitHub repository LEEI1337/phantom-neural-cortex (5 stars, last pushed 6mo ago), licensed MIT. It adds 7 tokens to every session and 182 once invoked, about $0.0000 per session on Opus 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.
Other commands, from other repositories
frontend
Injects context of all relevant cli files.
cleanup-back-to-main
Go back to main and clean up the branch.
spec-design
Create comprehensive technical design for a specification.
notebook-query
Query the notebook knowledge base (SQLite) built by /agy:notebook — precise, grounded, cited. Ask in natural language ("sum the amounts by category", "which docs mention 'Acme Corp'", "build a project timeline") or pass raw SQL. Read-only. Use this when you need exact aggregates/lookups across a document corpus…
tldr
Re-apply TLDR rules for this turn (verdict first, no filler).
ingest
Manually add knowledge to the Weaviate store.