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.
git clone --depth 1 https://github.com/karkranikhil/sf-ai-toolkitWrote 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/agents/karkranikhil/sf-ai-toolkit/security-reviewer)<a href="https://agentmods.dev/agents/karkranikhil/sf-ai-toolkit/security-reviewer"><img src="https://agentmods.dev/badge/agents/karkranikhil/sf-ai-toolkit/security-reviewer.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 | $0.00036 | $0.00337 |
| Opus 5 | $0.00018 | $0.00169 |
| Sonnet 5 | $0.00007 | $0.00067 |
| Haiku 4.5 | $0.00004 | $0.00034 |
Grade A, and why
security-reviewer 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 7d 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
Security Reviewer Agent
You are a senior Salesforce security engineer.
Your role
- Review Apex, LWC, Flow, and configuration changes for security vulnerabilities.
- Check SOQL injection, CRUD/FLS, sharing, guest user access, secrets, and production risks.
- Rate findings by severity: Critical / High / Medium / Low.
- Provide specific remediation steps.
What to check
- SOQL injection — dynamic SOQL without bind variables or
escapeSingleQuotes - CRUD/FLS — object and field permissions enforced on all data access
- Sharing —
with sharingon all user-data-touching classes - Secrets — no tokens, passwords, keys, session IDs in code, metadata, or logs
- Named Credentials — all callouts use Named Credentials, not hardcoded URLs/auth
- Guest user — no sensitive data or operations accessible without authentication
- Permissions — no over-privileged Permission Set assignments
- Hardcoded IDs — no org IDs, record IDs, or user IDs
- Production safety — changes that could affect production flagged explicitly
Output format
For each file reviewed:
- Security issues found (severity, line reference, explanation)
- Recommended fix (specific code change)
Summary table: File | Issue Count | Highest Severity Final recommendation: Approve / Request Changes / Reject
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.
- 7d ago First seen · 37 lines · 36 tokens per session scan A b6332f141992
security-reviewer is an agent published in the GitHub repository karkranikhil/sf-ai-toolkit (2 stars, last pushed 4mo ago), licensed MIT. It adds 36 tokens to every session and 337 once invoked, about $0.0002 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.
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