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 Snowflake-Labs/cocoplus --skill cococonvergegit clone --depth 1 https://github.com/Snowflake-Labs/cocoplusWrote 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/snowflake-labs/cocoplus/cococonverge)<a href="https://agentmods.dev/skills/snowflake-labs/cocoplus/cococonverge"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/cococonverge/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/snowflake-labs/cocoplus/cococonverge"><img src="https://agentmods.dev/badge/skills/snowflake-labs/cocoplus/cococonverge.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 | $0.00048 | $0.01718 |
| Opus 5.5 | $0.00019 | $0.00687 |
| Sonnet 5.5 | $0.00010 | $0.00344 |
| Haiku 4.5 | $0.00005 | $0.00172 |
Grade A, and why
cococonverge 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Objective
You are executing a CocoPivot command. When N CocoPods inspect the same codebase in parallel, they produce N separate findings lists — often the same underlying issue described three different ways from three different lenses. CocoPivot's discipline is to be the sole author of lifecycle/FINDINGS.md, so the developer has exactly one authoritative source for what needs addressing and in what order. Without CocoPivot, parallel pods produce parallel noise. With it, they produce coordinated signal.
Before proceeding, verify that .cocoplus/ exists. If not, output: "CocoPlus is not initialized. Run $pod init first." Then stop.
Commands
$pivot run
Use the cococonverge/pivot-merge contract in run mode. Read all pod output files produced by the most recent CocoFlow parallel: step execution (from pod-status.json), apply the three-pass deduplication algorithm below, assign priority tiers and effort estimates, and write lifecycle/FINDINGS.md and lifecycle/findings-state.json. If the upstream flow used on_partial: skip_partial, exclude PARTIAL pod outputs.
$pivot run --since <timestamp>
Use the cococonverge/pivot-merge contract in run mode and target only pod outputs that completed after <timestamp>. Useful for re-running convergence when additional pods have completed since the last run.
$pivot show
Display the current lifecycle/FINDINGS.md, grouped by priority tier. Include the Coverage Note section if any contributing pod was PARTIAL.
$pivot status
Read lifecycle/findings-state.json and display: total unique findings, count by priority tier (P1/P2/P3/P4), count by severity (BLOCKING/IMPORTANT/MINOR/ADVISORY), list of contributing pods with completion status (COMPLETE/PARTIAL/ERROR), and timestamp of the last convergence run.
$pivot clear
Archive the current FINDINGS.md to lifecycle/findings-archive/<timestamp>-FINDINGS.md and reset findings-state.json in preparation for a new convergence run.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 113 lines · 48 tokens per session scan A 97eb26af87d5
cococonverge is a skill published in the GitHub repository Snowflake-Labs/cocoplus (726 stars, last pushed 20d ago), licensed MIT. It adds 48 tokens to every session and 1,718 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 2026-09-03.
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