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 Cleo-Labs-IA/skills_library --skill packaging-traceabilitygit clone --depth 1 https://github.com/Cleo-Labs-IA/skills_libraryWrote 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/cleo-labs-ia/skills_library/packaging-traceability)<a href="https://agentmods.dev/skills/cleo-labs-ia/skills_library/packaging-traceability"><img src="https://agentmods.dev/badge/skills/cleo-labs-ia/skills_library/packaging-traceability/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/cleo-labs-ia/skills_library/packaging-traceability"><img src="https://agentmods.dev/badge/skills/cleo-labs-ia/skills_library/packaging-traceability.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 | $0.00094 | $0.02561 |
| Opus 5 | $0.00047 | $0.01281 |
| Sonnet 5 | $0.00019 | $0.00512 |
| Haiku 4.5 | $0.00009 | $0.00256 |
Grade A, and why
packaging-traceability 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 9d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Packaging Traceability
Resolve any product identifier -> the complete packaging bill-of-materials. Suppliers, quantities per material, packaging tier, origin, recyclability, recycled content. The upstream data layer that EPR, DPP, and PPWR all depend on.
This skill is the inbound data-resolution problem, not the disclosure: digital-product-passport produces the passport, packaging-compliance files the EPR declaration, sustainability-compliance reports recycled content -- but all three break if you cannot answer "what is this packaging actually made of, in what quantity, and where did it come from?" That answer is what authorities increasingly demand and what most brands cannot produce from a foreign batch code.
MCP Tools
# Search for traceability / reporting-granularity signals
mcp__claude_ai_Cleo_Insight__search_signals(q="packaging traceability", limit=25)
mcp__claude_ai_Cleo_Insight__search_signals(q="recycled content declaration", limit=25)
mcp__claude_ai_Cleo_Insight__search_signals(q="EPR eco-modulation", limit=25)
mcp__claude_ai_Cleo_Insight__search_signals(q="material composition reporting", limit=25)
# Pull the regulation that sets the granularity requirement
mcp__claude_ai_Cleo_Insight__get_regulation(id="<regulation-id>")
mcp__claude_ai_Cleo_Insight__list_regulations(limit=100)
# Resolve material -> HS code for cross-border reconciliation
mcp__claude_ai_CLEO_LEGAL_API__customs/classify
description: "<packaging material / component>"
Resolution Decision Tree
digraph {
rankdir=TB; node [shape=box style=rounded fontsize=10];
id [label="What identifier do you hold?" shape=diamond];
sku [label="Product reference / SKU"];
batch [label="Batch / lot number"];
formula [label="Formula / formulation code"];
bom [label="Resolve to packaging\nbill-of-materials (BOM)"];
tier [label="Split by tier:\nprimary / secondary /\ntertiary / service"];
comp [label="Per component: material,\nweight, supplier, origin,\nrecycled %, recyclable?"];
gap [label="Completeness check:\nany unknown supplier,\nquantity, or material?" shape=diamond];
chase [label="Chase the gap with\nthe supplier (PO, spec sheet,\nmaterial declaration)"];
feed [label="Feed downstream:\nEPR / DPP / recycled-content /\nrecyclability claim"];
id -> sku; id -> batch; id -> formula;
sku -> bom; batch -> bom; formula -> bom;
bom -> tier -> comp -> gap;
gap -> chase [label="gap"];
gap -> feed [label="complete"];
chase -> comp;
}
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.
- 9d ago First seen · 164 lines · 94 tokens per session scan A 530d87b1fa91
packaging-traceability is a skill published in the GitHub repository Cleo-Labs-IA/skills_library (1 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 2,561 once invoked, about $0.0005 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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