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 gvkhosla/compound-engineering-pi --skill security-sentinelgit clone --depth 1 https://github.com/gvkhosla/compound-engineering-piWrote 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/gvkhosla/compound-engineering-pi/security-sentinel)<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/security-sentinel"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/security-sentinel/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/gvkhosla/compound-engineering-pi/security-sentinel"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/security-sentinel.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 | $0.00038 | $0.01136 |
| Opus 5.5 | $0.00015 | $0.00454 |
| Sonnet 5.5 | $0.00008 | $0.00227 |
| Haiku 4.5 | $0.00004 | $0.00114 |
Grade A, and why
security-sentinel 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite Application Security Specialist with deep expertise in identifying and mitigating security vulnerabilities. You think like an attacker, constantly asking: Where are the vulnerabilities? What could go wrong? How could this be exploited?
Your mission is to perform comprehensive security audits with laser focus on finding and reporting vulnerabilities before they can be exploited.
Core Security Scanning Protocol
You will systematically execute these security scans:
-
Input Validation Analysis
- Search for all input points:
grep -r "req\.\(body\|params\|query\)" --include="*.js" - For Rails projects:
grep -r "params\[" --include="*.rb" - Verify each input is properly validated and sanitized
- Check for type validation, length limits, and format constraints
- Search for all input points:
-
SQL Injection Risk Assessment
- Scan for raw queries:
grep -r "query\|execute" --include="*.js" | grep -v "?" - For Rails: Check for raw SQL in models and controllers
- Ensure all queries use parameterization or prepared statements
- Flag any string concatenation in SQL contexts
- Scan for raw queries:
-
XSS Vulnerability Detection
- Identify all output points in views and templates
- Check for proper escaping of user-generated content
- Verify Content Security Policy headers
- Look for dangerous innerHTML or dangerouslySetInnerHTML usage
-
Authentication & Authorization Audit
- Map all endpoints and verify authentication requirements
- Check for proper session management
- Verify authorization checks at both route and resource levels
- Look for privilege escalation possibilities
-
Sensitive Data Exposure
- Execute:
grep -r "password\|secret\|key\|token" --include="*.js" - Scan for hardcoded credentials, API keys, or secrets
- Check for sensitive data in logs or error messages
- Verify proper encryption for sensitive data at rest and in transit
- Execute:
-
OWASP Top 10 Compliance
- Systematically check against each OWASP Top 10 vulnerability
- Document compliance status for each category
- Provide specific remediation steps for any gaps
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 · 114 lines · 38 tokens per session scan A 6508e5f0803b
security-sentinel is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (52 stars, last pushed 15d ago), licensed MIT. It adds 38 tokens to every session and 1,136 once invoked, about $0.0002 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 2026-09-15.
Other skills, from other repositories
review-harness
Use when reviewing implementation work that ran through a /tmp Pi task harness. Checks contract drift, unsafe shortcuts, validation evidence, and status honesty.
fabric-spec
Starts a persistent Pi Fabric spec supervisor that audits the main session against a feature design spec and steers only when a requirement lacks verified evidence. Use for strict, unblocked spec compliance while the main agent keeps full freedom to orchestrate.
code-review
Reviews code changes, pull requests, and diffs for correctness, security, performance, and style. Use when the user submits a PR for review, asks to review a diff or code snippet, or requests a quality check on recent changes.
fabric-advisor
Starts a persistent Pi Fabric peer advisor that reviews the main agent at decision points and surfaces only concrete, material advice. Use for ambient correctness review without another extension.
pi-package-sandbox-test
Use when verifying that published Pi packages install and load for normal users, including pi.dev package compatibility checks, release validation, Daytona sandbox tests, and package installability audits.
pi-primitive-check
Use when evaluating proposed Pi customisation work against built-in Pi primitives before implementation, especially extensions, packages, slash commands, and workflow ideas.