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 manishiitg/coding-agent-loop --skill inventory-risk-to-reviewed-replenishmentgit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/inventory-risk-to-reviewed-replenishment)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/inventory-risk-to-reviewed-replenishment"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/inventory-risk-to-reviewed-replenishment/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/manishiitg/coding-agent-loop/inventory-risk-to-reviewed-replenishment"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/inventory-risk-to-reviewed-replenishment.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 | $0.00025 | $0.00720 |
| Opus 5.5 | $0.00010 | $0.00288 |
| Sonnet 5.5 | $0.00005 | $0.00144 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
inventory-risk-to-reviewed-replenishment 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 20d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inventory Risk to Reviewed Replenishment
Outcome
Give a procurement owner one sourced, recomputable reorder or defer decision for an exact inventory item, location and supplier. Separate a later purchase order from supplier confirmation, physical transfer and received available stock.
When to use
Use when the merchant must decide whether and how much to buy from a supplier. Use Inventory Availability to Owner Action for a display or sync mismatch without purchasing. Handle one item/location/supplier in each artifact pair.
Discovery and user direction
Find existing Catalog & Merchandising Analyst and Replenishment Planner Crews, inventory authority, demand reports, supplier terms, open POs/transfers, budget policy, and procurement owner. Ask for the chosen demand window and safety stock. Show the route before Builder applies it. Selection copies pending setup; it orders nothing.
Required inputs
Bind store, market, product, variant, InventoryItem, destination Location, supplier/SKU, time window, available and distinct incoming units, backorders, demand units and days, lead and review days, safety stock, MOQ, case pack, unit cost and currency. Missing assumptions yield needs_information.
Plan and AgentWorks tools
Catalog emits inventory-availability-exception/v1 for the exact item/location; validate it using the existing inventory contract or scripts/validate_handoff.py --signal-only <signal.json>. Replenishment Planner re-reads incoming, open POs, supplier terms and demand, then emits replenishment-review/v1; validate the pair before procurement review. Calculate target and shortage in integer units, round to pack/MOQ, and calculate cost in minor units. A separate approved route may create a PO and later record transfer receipt. A webhook triggers a re-read, not a purchase.
Knowledge and persistence
Keep item-location-supplier-window case and action IDs, source times, demand definition, incoming/PO deduplication, terms version, owner decision, PO/supplier confirmation, transfer receipt, and location-level stock verification. Re-read before repeats to prevent double orders.
What ships with it
8 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.
- examples/invalid-replenishment-review.json 1.9 KB
- examples/inventory-signal.json 749 B
- examples/replenishment-review.json 2.2 KB
- playbook.json 4.5 KB
- references/team-and-handoffs.md 3.7 KB
- scripts/test_validate_handoff.py 4.7 KB runs code
- scripts/validate_handoff.py 8.7 KB runs code
- SETUP.json 2.6 KB
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.
- 20d ago First seen · 48 lines · 25 tokens per session scan A d1f7fdbfc1c0
inventory-risk-to-reviewed-replenishment is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 25 tokens to every session and 720 once invoked, about $0.0001 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 2026-09-27.
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