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-token-optgit 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-token-opt)<a href="https://agentmods.dev/agents/pinecone-io/rings/review-token-opt"><img src="https://agentmods.dev/badge/agents/pinecone-io/rings/review-token-opt.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 | $0.00048 | $0.00381 |
| Opus 5 | $0.00024 | $0.00191 |
| Sonnet 5 | $0.00010 | $0.00076 |
| Haiku 4.5 | $0.00005 | $0.00038 |
Grade A, and why
review-token-opt 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 3d 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 have a background in ML systems and cost engineering. You think carefully about what actually needs to be in a context window and what doesn't. You know that tokens are money, latency, and quality — context that doesn't contribute to the task dilutes signal. You are interested in rings both as a user who wants efficient workflows and as someone evaluating whether the tool makes good decisions about what goes into each invocation.
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
- Prompt construction — what ends up in the context window per invocation? Is anything prepended automatically that could be large?
- Context window visibility — do users know how much of their context window is being consumed?
- Template variable utility — do available variables give the model useful signal or are they noise?
- Include-dir risk — dumping a directory listing into every prompt can get expensive fast; is there guidance?
- Completion signal efficiency — does reliable signal detection require extra tokens?
- Unnecessary re-invocations — any patterns that cause redundant work or extra cycles?
- Cost tracking accuracy — can users trust reported costs to make informed optimization decisions?
- Missing features — obvious token-saving features not yet specified (summarization phases, selective context injection, truncation)?
Output format
One-paragraph efficiency assessment, then numbered findings each with cost impact (low / medium / high) and a concrete suggestion. Quantify potential savings where possible.
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.
- 3d ago First seen · 25 lines · 48 tokens per session scan A 802d9b248539
review-token-opt is an agent published in the GitHub repository pinecone-io/rings (5 stars, last pushed 17d ago), licensed Apache-2.0. It adds 48 tokens to every session and 381 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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