What makes QSR Labor Leak Auditor notable?

1.5K downloads. Trust evidence available

How should QSR Labor Leak Auditor 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 Labor Leak Auditor

Real-time labor decision support for restaurant and franchise operators with summary-first mobile-optimized output. All V3 capabilities — surfaced events, state control, goal tracking, recovery planning, forward planning, event-aware comparisons — plus executive-summary-first formatting, math hidden by default, standardized output structure, and concise correction handling. Designed for fast mobile operator use on the shift floor. Built by a franchise GM with 16 years in QSR operations.

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.5k

Updated

Oct 10, 2026

Version

3.1.4

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.5K 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: 1.5K downloadsadoption · observed Oct 10, 2026
Latest release: 3.1.4release · observed Sep 21, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s176n3ns9yxm5bkwfzy1px199x842m27:qsr-labor-leak-auditor

Install using `clawhub skill install s176n3ns9yxm5bkwfzy1px199x842m27:qsr-labor-leak-auditor` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/mcphersonai/qsr-labor-leak-auditor before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-mcphersonai-qsr-labor-leak-auditor/snapshot"

Documentation

CLAWHUB

144,618 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: qsr-labor-leak-auditor
version: 3.1.4
description: Real-time labor decision support for restaurant and franchise operators with summary-first mobile-optimized output. All V3 capabilities — surfaced events, state control, goal tracking, recovery planning, forward planning, event-aware comparisons — plus executive-summary-first formatting, math hidden by default, standardized output structure, and concise correction handling. Designed for fast mobile operator use on the shift floor. Built by a franchise GM with 16 years in QSR operations.
license: CC-BY-NC-4.0
tags:
  - restaurant
  - franchise
  - operations
  - labor
  - scheduling
  - payroll
  - qsr
  - cost-control
  - decision-support
  - goal-tracking
  - mobile-first
---

## 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-labor-leak-auditor)

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

# QSR Labor Leak Auditor
**v3.1.4 · McPherson AI · San Diego, CA**
[mcphersonai.com](https://mcphersonai.com)

You are a real-time labor decision support assistant for a restaurant or franchise location. Your job goes beyond tracking labor cost — you help the operator understand where they stand, whether they are on track for the week, what to do when they are not, and how to plan tomorrow. You maintain awareness of stored operating context and surface it at the moment it affects a labor read.

**V3.1 adds a presentation layer:** your default output is a short executive summary. Detailed math and worksheets are hidden unless the operator asks. Every response is designed for fast reading on a phone screen during a busy shift.

Labor is the second biggest controllable expense after food cost. Most operators don't know they're over on labor until the weekly P&L hits — by then the hours are worked and the money is spent. This skill catches overruns while there's still time to act, tracks them against real savings goals, and converts problems into practical recovery paths.

**Recommended models:** This skill involves daily math, state tracking, goal comparison, and contextual reasoning. Works best with capable models (Claude, GPT-4o, Gemini Pro or higher).

---

## DATA STORAGE

**Daily entry format** — store each daily entry as:
```
[DATE] | [DAY OF WEEK] | [SALES: $X] | [LABOR HOURS: X] | [LABOR COST: $X] | [LABOR %: X%] | [TARGET %: X%] | [VARIANCE: +/-X%] | [FLAGS: list or "none"] | [EVENT TAGS: list or "none"] | [NOTES: text or "none"] | [STATE: active / voided] | [ENTRY VERSION: X]
```

**Weekly goal tracking format** — maintain a running weekly record:
```

README.md

# QSR Labor Leak Auditor
**v3.1.4 · McPherson AI · San Diego, CA**

AI-powered weekly labor cost auditor for QSR operators: tracks labor as a percentage of revenue, catches clock padding and scheduling drift, and flags mid-week risks before payroll closes.

**v2 update:** now uses contextual windows like catering, promotions, events, and weather before recommending labor cuts, with manager override and a full audit trail.

## 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-labor-leak-auditor)

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

---

## Overview

QSR Labor Leak Auditor is a weekly labor monitoring skill built for restaurant operators who need tighter control over labor cost before payroll is locked in.

It is designed to help managers identify labor inefficiency early in the week, not after the damage is already done.

This skill reviews labor performance in context and highlights the most likely causes of drift, overstaffing, and avoidable wage leakage so store leadership can take corrective action while there is still time to act.

It is built from real operating experience inside high-volume QSR environments.

---

## What It Does

QSR Labor Leak Auditor functions as an operational labor cost watchdog for store leadership.

It helps operators:

- Track labor as a percentage of revenue by day
- Catch mid-week labor drift before payroll closes
- Identify possible clock padding and scheduling inefficiency
- Flag overstaffing relative to sales performance
- Distinguish normal labor pressure from avoidable waste
- Surface patterns that managers may miss during busy weeks
- Recommend corrective action before the week ends

Rather than simply reporting numbers, this skill is designed to think like an experienced QSR operator reviewing the labor story behind the metrics.

---

## Core Use Cases

### 1. Daily Labor-to-Sales Tracking
Monitors labor performance against revenue trends across the week to identify when the store is falling out of alignment.

### 2. Mid-Week Risk Detection
Provides an actionable warning while the operator still has time to reduce unnecessary hours, rebalance staffing, or tighten shift execution.

### 3. Clock Padding and Labor Leak Review
Flags patterns that may suggest idle labor, weak deployment, long overlaps, or unnecessary scheduled coverage.

### 4. Scheduling Drift Analysis
Detects when staffing patterns begin to separate from actual business volume, creating preventable labor loss.

### 5. Contextual Audit Support
Evaluates labor pressure with awareness that not every spike is a true problem. Weather, events, promos, catering, or unus

_meta.json

{
  "ownerId": "kn77bzntvd26te0kr70gfmnt3s83798q",
  "slug": "qsr-labor-leak-auditor",
  "version": "3.1.4",
  "publishedAt": 1790034409111
}

skill-card.md

## Description:

QSR Labor Leak Auditor provides real-time labor decision support for restaurant and franchise operators, with concise daily labor reads, week-to-date goal tracking, and recovery planning for payroll-week decisions.

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 interpret sales and labor inputs, track week-to-date labor against targets, and produce concise recovery actions before payroll closes.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Store-level sales, labor cost, weekly goal, and audit context may be persisted by the configured store memory engine.

Mitigation: Review the memory engine retention, deletion, authentication, authorization, and access-control settings before deployment.

Risk: Labor recommendations can affect staffing decisions if treated as automatic instructions.

Mitigation: Use the output as decision support, keep operator review and override context, and confirm operational constraints before changing schedules.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/mcphersonai/skills/qsr-labor-leak-auditor)
- [McPherson AI](https://mcphersonai.com)

## Skill Output:

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

**Output Format:** [Markdown and structured text records]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [In-chat summaries with optional detailed math; persistent records depend on the configured store memory engine.]

## Skill Version(s):

3.1.4 (source: frontmatter, 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 redistribution

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 redistribution.

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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