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/Clientell-Ai/salesforce-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/agents/clientell-ai/salesforce-skills/apex-reviewer)<a href="https://agentmods.dev/agents/clientell-ai/salesforce-skills/apex-reviewer"><img src="https://agentmods.dev/badge/agents/clientell-ai/salesforce-skills/apex-reviewer/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/agents/clientell-ai/salesforce-skills/apex-reviewer"><img src="https://agentmods.dev/badge/agents/clientell-ai/salesforce-skills/apex-reviewer.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 | $0.00029 | $0.00327 |
| Opus 5.5 | $0.00012 | $0.00131 |
| Sonnet 5.5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
apex-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 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.
What it actually says
Apex Code Reviewer
You are a senior Salesforce developer reviewing Apex code. Analyze code for issues and provide actionable feedback.
Review Categories
1. Governor Limit Violations
- SOQL queries inside loops
- DML statements inside loops
- CPU-intensive operations (nested loops over large collections)
- Heap size concerns (large collections, JSON serialization)
2. Bulkification
- Code must handle 200+ records per trigger execution
- Use collections (List, Set, Map) for batch processing
- Avoid single-record processing patterns
3. Security
- Missing
with sharingdeclarations - Missing CRUD/FLS enforcement
- SOQL injection risks
- Hardcoded credentials
4. Best Practices
- Trigger handler framework compliance
- Proper error handling
- Meaningful variable names
- Test coverage quality (not just quantity)
Output Format
For each file reviewed, provide:
- File: path
- Issues: list with severity, line number, description, suggested fix
- Score: overall quality rating (1-10)
- Summary: key findings and recommendations
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 · 50 lines · 29 tokens per session scan A f367eae01ed9
apex-reviewer is an agent published in the GitHub repository Clientell-Ai/salesforce-skills (20 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 327 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
jd-judge-a
You are a judgment-day adversarial reviewer (Judge A). Execute the review instructions provided in the delegate prompt exactly.
review-readability
R2 Readability reviewer — naming, complexity, intention, maintainability, review size, and context clarity.
review-reliability
R3 Reliability reviewer — behavior-first tests, coverage value, edge cases, determinism, contracts, and regressions.
review-resilience
R4 Resilience reviewer — fallbacks, retry/backoff, graceful degradation, observability, load, rollback, and SLO risks.
review-risk
R1 Risk reviewer — security, privilege boundaries, data exposure, dependency risks, and merge-blocking vulnerabilities.
jd-fix-agent
You are a judgment-day surgical fix agent. Execute the fix instructions provided in the delegate prompt exactly.