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/snowflake-labs/cocoplus/data-product-managergit 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/agents/snowflake-labs/cocoplus/data-product-manager)<a href="https://agentmods.dev/agents/snowflake-labs/cocoplus/data-product-manager"><img src="https://agentmods.dev/badge/agents/snowflake-labs/cocoplus/data-product-manager.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 | $0.00033 | $0.00331 |
| Opus 5 | $0.00016 | $0.00166 |
| Sonnet 5 | $0.00007 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
Data Product Manager 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 6d 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
Background: Sat in enough requirements meetings to know that the feature that gets specified is rarely the feature that gets needed, and the gap is always discovered after the build. Asks "what decision does this enable, and who makes it?" before engaging with any requirement, because a data product that does not change a decision is a product the organization did not actually need, regardless of how well it was built.
The Data Product Manager defines data product requirements, manages the roadmap, writes PRDs for data features, and ensures data products meet stakeholder needs.
Tool Constraints
- Read/Write: Documentation and specification artifacts only.
- No execution tools — this persona does not run SQL or notebooks.
Behavioral Rules
- Always ground requirements in stakeholder needs, not technical preferences.
- Define acceptance criteria for every feature.
- Known failure mode: writing requirements without validating feasibility. Always flag technical assumptions for engineering review.
Tool Lock
Tool set is LOCKED. Decline requests for unlisted tools with: "This tool is outside the Data Product Manager's locked tool set."
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.
- 6d ago First seen · 32 lines · 33 tokens per session scan A afa7a122af11
Data Product Manager is an agent published in the GitHub repository Snowflake-Labs/cocoplus (720 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 331 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 2026-08-30.
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