What makes QSR Ghost Inventory Hunter notable?

1.4K downloads. Trust evidence available

How should QSR Ghost Inventory Hunter be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

QSR Ghost Inventory Hunter

Identifies unaccounted inventory loss in restaurant operations by cross-referencing sales volume against theoretical recipe yields. Pinpoints whether missing product is theft, over-portioning, unrecorded waste, or prep errors. Built by a QSR GM with 16 years in restaurant operations. Skill: QSR Ghost Inventory Hunter Owner: mcphersonai Summary: Identifies unaccounted inventory loss in restaurant operations by cross-referencing sales volume against theoretical recipe yields. Pinpoints whether missing product is theft, over-portioning, unrecorded waste, or prep errors. Built by a QSR GM with 16 years in restaurant operations. Tags: latest:1.0.3 Version history: v1.0.3 | 2026-09-21T23:46:59.997Z | a

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

1.0.3

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.3release · observed Sep 21, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s176n3ns9yxm5bkwfzy1px199x842m27:qsr-ghost-inventory-hunter

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-mcphersonai-qsr-ghost-inventory-hunter/snapshot"

Documentation

CLAWHUB

76,625 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: qsr-ghost-inventory-hunter
version: 1.0.3
description: Identifies unaccounted inventory loss in restaurant operations by cross-referencing sales volume against theoretical recipe yields. Pinpoints whether missing product is theft, over-portioning, unrecorded waste, or prep errors. Built by a QSR GM with 16 years in restaurant operations.
license: CC-BY-NC-4.0
tags:
  - restaurant
  - franchise
  - operations
  - inventory
  - food-cost
  - shrink
  - waste
  - qsr
  - theft-prevention
---

## Building with AI agents? Get started with Observa

See observed runtime activity, review what governance WOULD have done in SHADOW mode, and preserve the evidence behind it across OpenClaw and supported n8n workflows.

[**Get started with Observa →**](https://mcphersonai.com/observa/getting-started?utm_source=clawhub&utm_medium=skill&utm_campaign=observa-getting-started&utm_content=qsr-ghost-inventory-hunter)

*SHADOW ONLY · AUTHORITY NONE · ENFORCEMENT OFF. Publisher notice only; this QSR skill’s operating behavior, data handling, and license are unchanged.*

# QSR Ghost Inventory Hunter
**v1.0.3 · McPherson AI · mcphersonai.com · San Diego, CA**

You are an inventory variance investigator for a restaurant or franchise location. Your job is to find "ghost inventory" — product that disappeared from the shelf but never appeared on a sales receipt or a waste log. It was ordered, it was received, but it's gone — and nobody can account for where it went.

The food cost diagnostic (skill #2) tells the operator their COGS is high. This skill tells them exactly where the product went. It's the difference between knowing you have a problem and knowing what the problem actually is.

**Recommended models:** This skill involves multi-step reasoning across sales data, recipe yields, and inventory counts. Works best with capable models (Claude, GPT-4o, Gemini Pro or higher).

---

## DATA STORAGE

**Memory format** — store each investigation as:
```
[DATE] | [ITEM INVESTIGATED] | [THEORETICAL USAGE: X units] | [ACTUAL USAGE: X units] | [VARIANCE: X units / $X] | [PROBABLE CAUSE: over-portion/waste/theft/prep-error] | [ACTION: text] | [FOLLOW-UP: date or "none"]
```

---

## FIRST-RUN SETUP

Ask these questions before running the first investigation:

1. **What are your top 5 highest-cost inventory items?** (usually proteins, cheese, specialty ingredients — the items where variance hurts the most)
2. **Do you have recipe cards with defined yields?** (e.g., "one case of turkey yields 80 sandwiches" — if yes, this is the foundation of the analysis. If no, help the operator build rough yields for their top items.)
3. **How often do you take inventory counts?** (weekly, biweekly, monthly — weekly is ideal for this skill)
4. **Do you track waste separately from sales?** (waste log, spoilage log, or nothing)
5. **How do you receive deliveries?** (do you verify quantities against invoices on arrival, or just sign and put it away)

Confirm:
> **Setup Complete** — Top it

README.md

# QSR Ghost Inventory Hunter

**v1.0.3 · McPherson AI · San Diego, CA**  
[mcphersonai.com](https://mcphersonai.com)

## Building with AI agents? Get started with Observa

Observa shows supported OpenClaw and n8n runtime activity, what governance WOULD have done in SHADOW mode, and the evidence behind it.

[**Get started with Observa →**](https://mcphersonai.com/observa/getting-started?utm_source=github&utm_medium=skill-readme&utm_campaign=observa-getting-started&utm_content=qsr-ghost-inventory-hunter)

*SHADOW ONLY · AUTHORITY NONE · ENFORCEMENT OFF. This publisher notice does not change the QSR skill itself.*

QSR Ghost Inventory Hunter helps restaurant and franchise operators identify unaccounted inventory loss by comparing theoretical recipe usage against actual inventory movement.

It is designed to answer a simple but expensive question:

**If the product was ordered and received, but never sold or logged as waste, where did it go?**

This skill investigates the gap between:
- sales volume
- recipe yields
- inventory counts
- deliveries received
- waste tracking

It helps determine whether missing product is most likely caused by:
- over-portioning
- unrecorded waste
- prep error
- receiving discrepancy
- theft

## What it does

This skill walks an operator through a focused inventory variance investigation for one item at a time.

It:
- calculates theoretical product usage from sales mix and recipe portions
- calculates actual product usage from beginning inventory, deliveries, and ending inventory
- identifies the variance between the two
- converts the variance into estimated dollar loss
- helps diagnose the most likely cause
- generates a structured ghost inventory report
- tracks patterns across repeat investigations

## Best use cases

Use this skill when:
- food cost is elevated but the cause is unclear
- a high-cost item runs out faster than expected
- inventory counts do not match what should be on hand
- waste tracking is incomplete
- receiving accuracy is in question
- the operator suspects shrink or product loss

## Example investigation

Example:

- 400 turkey sandwiches sold
- 3 oz turkey per sandwich
- theoretical usage = 1,200 oz = 75 lbs

Inventory movement:

- starting inventory = 100 lbs
- deliveries = 50 lbs
- ending inventory = 60 lbs
- actual usage = 90 lbs

Result:

- ghost inventory = 15 lbs
- if turkey costs $4.20/lb, estimated unexplained loss = $63.00

That gives the operator a concrete starting point for investigation instead of a vague feeling that food cost is too high.

## Why it matters

Most operators know when food cost is off.

Fewer know whether the cause is:
- line over-portioning
- prep waste
- unlogged spoilage
- short deliveries
- or actual theft

This skill helps narrow that down with numbers.

## Works best with

This skill pairs well with:

- **qsr-food-cost-diagnostic** — identifies that a food cost variance exists
- **qsr-weekly-pl-storyteller** — helps connect inventory loss back to the weekly f

_meta.json

{
  "ownerId": "kn77bzntvd26te0kr70gfmnt3s83798q",
  "slug": "qsr-ghost-inventory-hunter",
  "version": "1.0.3",
  "publishedAt": 1790034419997
}

skill-card.md

## Description:

Identifies unaccounted inventory loss in restaurant operations by cross-referencing sales volume against theoretical recipe yields.

This skill is ready for commercial/non-commercial use.

## Publisher:

[mcphersonai](https://clawhub.ai/user/mcphersonai)

### License/Terms of Use:

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

## Use Case:

Restaurant and franchise operators use this skill to investigate unexplained inventory variance for one high-cost item at a time, comparing sales mix, recipe yields, inventory counts, deliveries, waste records, and cost figures to identify likely causes and next actions.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Users may share sensitive restaurant sales, inventory, delivery, waste, or cost figures with the agent.

Mitigation: Use the skill only with data the operator is comfortable sharing with the selected agent and model environment.

Risk: Inventory variance analysis could be misread as proof of employee misconduct.

Mitigation: Treat the output as an operational diagnostic, review the underlying business records, and avoid naming or accusing individuals based only on the skill's report.

## Reference(s):

- [QSR Ghost Inventory Hunter on ClawHub](https://clawhub.ai/mcphersonai/skills/qsr-ghost-inventory-hunter)
- [Skill README](README.md)
- [Skill Prompt](SKILL.md)
- [McPherson AI](https://mcphersonai.com)

## Skill Output:

**Output Type(s):** [Text, Markdown, Guidance]

**Output Format:** [Markdown report and conversational diagnostic guidance]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Uses user-provided sales, inventory, delivery, waste, and cost figures; no external system integration is required.]

## Skill Version(s):

1.0.3 (source: frontmatter and server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

LICENSE

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

Copyright (c) 2026 Blake McPherson / McPherson AI

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

You are free to:

- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material

Under the following terms:

- Attribution — You must give appropriate credit
- NonCommercial — You may not use the material for commercial purposes

Additional License Clarification:

For the purposes of this license, using this skill within your own business, restaurant, franchise, or internal operations is permitted and is not considered commercial use requiring separate permission.

Commercial redistribution means:

- Reselling this skill
- Repackaging this skill as a paid product
- Offering it as part of a competing commercial platform
- Redistributing modified or unmodified versions for direct commercial sale or licensing

This clarification is intended to allow practical operational use while protecting the original work from unauthorized resale or platform exploitation.

Full license text:
https://creativecommons.org/licenses/by-nc/4.0/

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