IntermediateAlireza Rezvani

Procurement Optimizer

Procurement Optimizer is an ecommerce AI skill for Alireza Rezvani, built for teams working with Codex, Claude Code, OpenClaw. Use it to prioritize stocking,…

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Supported Platforms
Codex · Claude Code · OpenClaw
01

What this Skill does

You need to prioritize stocking, replenishment, or purchasing decisions. Validate one concrete path first: Annual SaaS audit identifying top-5 spend-growth categories with Pareto breakdown; Supplier base rationalization — merging duplicate-function tools with risk-flagged….… Start with a small test around “Annual SaaS audit identifying top-5 spend-growth categories with Pareto breakdown”, then check whether “Supplier base rationalization — merging duplicate-function tools with risk-flagged consolidation plan” fits the way your team actually works.

02

What makes it different

01

Turns customer feedback into structured output

The source asks the model to group, classify, answer, or prioritize review feedback rather than treating every comment as an isolated case.

02

Structures the analysis before making a recommendation

The source asks for analysis, classification, ranking, or scoring before it reaches a conclusion or next action.

03

Before you use it

Source file or structured data

This instruction refers to file or tabular input. Prepare the requested file and confirm that the model you use can read it.

Python runtime

The source includes a Python command or script. A compatible local Python environment is required for that part of the workflow.

04

No installation needed

Copy and paste into a model chat
  1. Expand and copy the complete original Skill.md below.
  2. Open a new conversation in a compatible AI model, then paste it into the chat box.
  3. Add verified task details, run one low-risk example, and review the result before using it in store operations.
05

Original Skill.md

The complete source is shown below. Copy it from the top right to use it.

You are Head of Procurement running the annual category review. Fill the spend intake template with line items. Run spend_categorizer.py --profile <tech-startup|scaleup|enterprise> for UNSPSC-aligned categorization, Pareto, and YoY growth. Run purchasing_cycle_analyzer.py to flag bottleneck categories where cycle time exceeds 2× cross-category median (Goldratt). Run supplier_consolidation.py for duplicate-function clusters — refuse single-source for tier-1 without documented break-glass. Flag renewal clusters (≥3 contracts same month). Synthesize: top growth categories, bottlenecks, consolidation opportunities with estimated savings and risk flags. Estimate savings as: cluster spend minus winner spend minus migration costs.
06

Get started

Starter prompts for the main use cases—copy and use them directly.

01

Start with one real task

Do not begin with a store-wide rollout. Pick one reversible task where Procurement Optimizer can help you plan inventory, purchasing, capacity, suppliers, and replenishment. Use this when the input boundary, owner, and one primary measure from forecast error, stockout rate, excess stock, cash tied up, and service level are written down.

Show prompt and variablesHide prompt and variables
Use the Skill above to help me with this task: Start with one real task.

Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]

Do not begin with a store-wide rollout. Pick one reversible task where Procurement Optimizer can help you plan inventory, purchasing, capacity, suppliers, and replenishment.

Return a practical result and clearly flag anything that needs human review.

Replace these variables

[TASK_DETAILS]
The facts, context, or source material for this task.
[CONSTRAINTS]
Replace this placeholder with your verified store-specific information.
02

Prepare the input and guardrails

Collect only the clean SKU history, lead times, current stock, purchase constraints, and margin assumptions needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.

Show prompt and variablesHide prompt and variables
Use the Skill above to help me with this task: Prepare the input and guardrails.

Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]

Collect only the clean SKU history, lead times, current stock, purchase constraints, and margin assumptions needed for this test. Remove unrelated personal data and state which actions must never run automatically.

Return a practical result and clearly flag anything that needs human review.

Replace these variables

[TASK_DETAILS]
The facts, context, or source material for this task.
[CONSTRAINTS]
Replace this placeholder with your verified store-specific information.
03

Inspect the source Skill, then run it

Read the source, installation method, and permission notes before adding Procurement Optimizer to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a inventory or purchasing recommendation that a responsible operator can inspect, and it stayed inside the approved boundary.

Show prompt and variablesHide prompt and variables
Use the Skill above to help me with this task: Inspect the source Skill, then run it.

Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]

Read the source, installation method, and permission notes before adding Procurement Optimizer to a separate test project. Keep commands and Skill text exactly as published.

Return a practical result and clearly flag anything that needs human review.

Replace these variables

[TASK_DETAILS]
The facts, context, or source material for this task.
[CONSTRAINTS]
Replace this placeholder with your verified store-specific information.
04

Review it against a baseline

Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when forecast error, stockout rate, excess stock, cash tied up, and service level has a pre-test baseline, and errors and exceptions are logged separately.

Show prompt and variablesHide prompt and variables
Use the Skill above to help me with this task: Review it against a baseline.

Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]

Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time.

Return a practical result and clearly flag anything that needs human review.

Replace these variables

[TASK_DETAILS]
The facts, context, or source material for this task.
[CONSTRAINTS]
Replace this placeholder with your verified store-specific information.
07

Risks and operating notes

Verify commercial terms before acting

Any price, discount, cost, or margin recommendation is only as current as the values you provide. Recheck live prices, tax, shipping, and margin rules before publishing or sending an offer.

Treat review patterns as hypotheses to test

The instruction can group and prioritize feedback, but repeated wording is not proof of a product defect or customer-wide preference. Check the underlying sample before changing a product, policy, or campaign.

Community rating results

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Task effectiveness
Setup and ease of use
Reliability and guardrails
Documentation clarity
Time to first useful result
Author / maintainer

Alireza Rezvani

HealthTech CTO and open-source maintainer focused on applied AI, agentic coding, and practical skills for product, research, growth, and operations teams.

Risk, permissions, and limitations

Review third-party permission scopes before providing store data. Never paste payment credentials, customer passwords, or unnecessary personal data into a model. Outputs must be checked by the operator responsible for the workflow.

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