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 asgard-ai-platform/skills --skill ecom-inventory-healthgit clone --depth 1 https://github.com/asgard-ai-platform/skillsWrote 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/asgard-ai-platform/skills/ecom-inventory-health)<a href="https://agentmods.dev/skills/asgard-ai-platform/skills/ecom-inventory-health"><img src="https://agentmods.dev/badge/skills/asgard-ai-platform/skills/ecom-inventory-health/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/asgard-ai-platform/skills/ecom-inventory-health"><img src="https://agentmods.dev/badge/skills/asgard-ai-platform/skills/ecom-inventory-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.01266 |
| Opus 5 | $0.00047 | $0.00633 |
| Sonnet 5 | $0.00019 | $0.00253 |
| Haiku 4.5 | $0.00009 | $0.00127 |
Grade A, and why
ecom-inventory-health 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- "ecom-inventory-health" — 92% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inventory Health Analysis
Overview
Inventory health balances two risks: stockouts (lost sales, unhappy customers) and overstock (carrying costs, obsolescence). This skill provides tools to measure, classify, and optimize inventory levels.
Framework
IRON LAW: Not All SKUs Deserve Equal Attention
ABC classification shows that ~20% of SKUs drive ~80% of revenue.
Treat A-items (top 20% revenue) with tight control and frequent review.
C-items (bottom 50% revenue) get simple rules and less attention.
Equal treatment of all SKUs wastes resources on low-impact items.
Key Metrics
| Metric | Formula | Healthy Range |
|---|---|---|
| Inventory Turnover | COGS / Avg Inventory | 4-12x/year (industry-dependent) |
| Days of Inventory (DOI) | 365 / Inventory Turnover | 30-90 days |
| Stockout Rate | Stockout incidents / Total demand occasions | < 2-5% |
| Fill Rate | Orders filled completely / Total orders | > 95% |
| Carrying Cost | Avg Inventory × Carrying Cost % (typically 20-30%/year) | Minimize |
| Dead Stock % | Items with zero sales in 6+ months / Total SKUs | < 10% |
ABC Classification
| Class | Revenue % | SKU % | Strategy |
|---|---|---|---|
| A | ~80% | ~20% | Tight control, frequent review, safety stock optimized |
| B | ~15% | ~30% | Moderate control, periodic review |
| C | ~5% | ~50% | Simple rules, min/max levels, consider dropping |
Safety Stock Calculation
Safety Stock = Z × σ_d × √(Lead Time)
Where:
- Z = service level factor (1.65 for 95%, 2.33 for 99%)
- σ_d = standard deviation of daily demand
- Lead Time = supplier lead time in days
Reorder Point
Reorder Point = (Average Daily Demand × Lead Time) + Safety Stock
Diagnosis Steps
Phase 1: Overall Health Check
- Calculate turnover and DOI for total inventory
- Compare to industry benchmarks
- Identify trend: improving or deteriorating?
Phase 2: ABC Classification
- Rank all SKUs by revenue contribution
- Classify into A/B/C
- Check: are A-items well-stocked? Are C-items over-stocked?
What ships with it
3 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.
- 9d ago First seen · 124 lines · 94 tokens per session scan A 1d38f3587fa1
ecom-inventory-health is a skill published in the GitHub repository asgard-ai-platform/skills (228 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 1,266 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 2026-09-03.
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