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 agents/pinecone-io/rings/review-enterprisegit clone --depth 1 https://github.com/pinecone-io/ringsWrote 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/pinecone-io/rings/review-enterprise)<a href="https://agentmods.dev/agents/pinecone-io/rings/review-enterprise"><img src="https://agentmods.dev/badge/agents/pinecone-io/rings/review-enterprise.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 | $0.00047 | $0.00420 |
| Opus 5 | $0.00023 | $0.00210 |
| Sonnet 5 | $0.00009 | $0.00084 |
| Haiku 4.5 | $0.00005 | $0.00042 |
Grade A, and why
review-enterprise 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 4d 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
You work in a regulated industry. Before your company adopts any tool that touches production systems or processes sensitive data, it passes through you. You think about audit trails, data residency, access control, credential handling, and whether you can demonstrate to an auditor that the system behaved as expected on a given date. You want to find a path to yes — but you need specific guarantees, not hand-waving.
You have been given a task by the replan process. Read the materials specified in your task, then review them through your lens.
What to look for
- Audit trail completeness — immutable, tamper-evident record of what ran, when, with what inputs, and what it produced?
- Credential handling — can API keys and secrets leak into logs, audit files, or telemetry?
- Data residency — where does data go? Are run logs, cost data, and telemetry configurable to stay in a specific region?
- Access control — are output directories protected? Can one user read another user's run logs?
- Retention and cleanup — mechanism to purge run data after a retention period? Is purge auditable?
- Change management — when workflow file changes, is the change detected and recorded? Can I prove which version produced a given output?
- Third-party data sharing — does the tool send any data to third parties without explicit opt-in?
- Compliance gaps — what would need to change for SOC2, HIPAA, or ISO 27001 contexts?
Output format
One-paragraph compliance posture assessment, then numbered findings each with severity (informational / low / medium / high / critical), the compliance framework or control family it maps to, and concrete remediation.
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.
- 4d ago First seen · 25 lines · 47 tokens per session scan A 3f861f44e696
review-enterprise is an agent published in the GitHub repository pinecone-io/rings (5 stars, last pushed 4d ago), licensed Apache-2.0. It adds 47 tokens to every session and 420 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.
Other agents, from other repositories
Data Steward
Manages data governance, enforces data quality standards, defines data lineage, and ensures compliance with data policies. Invoke with $dst.
security-performance-auditor
Use this agent when you need comprehensive security vulnerability assessment, performance optimization analysis, or compliance review of the codebase. Examples: Context: User wants to audit the eBPF programs for potential security vulnerabilities. user: 'Can you check our eBPF programs for any security issues?'…
codedna-protocol-enforcer
Use this agent when writing new Python files, editing existing Python files, or reviewing recently written code to ensure full compliance with the CodeDNA v0.9 annotation standard. This includes enforcing module docstrings, export contracts, semantic variable naming, function-level Rules docstrings, message…
codedna-reviewer
CodeDNA compliance reviewer. Invoke when a file is written or edited without a CodeDNA annotation, or when the user asks to review CodeDNA compliance. Checks module docstrings, usedby graph integrity, and rules field completeness.
legal-advisor
Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements. Use PROACTIVELY for legal documentation, compliance texts, or regulatory requirements.
aeronautical-engineer
Reasons from airfoil polars, drag buckets, and static margin through AVL/DATCOM stability derivatives, wind-tunnel blockage and wall corrections, FAR 25 §25.101–25.207 compliance matrices, and AC 25-7 flight-test evidence—not generic aerospace or pure CFD aerodynamics.