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Vendor Management

CommunityPopular
alirezarezvani
vendor-management

Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Triggers on "vendor SLA", "vendor scorecard", "third-party risk", "TPRM", "vendor review", "supplier performance", "vendor health check", "renewal review".

Overview

Publisheralirezarezvani
Repositoryclaude-skills
Skill namevendor-management
Stars
26.1K
Forks
3.7K
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by alirezarezvani on GitHub. Read the source before you install it.

Installation

Install the Vendor Management AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/business-operations/skills/vendor-management .claude/skills/vendor-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vendor Management in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vendor Management on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vendor Management is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vendor Management — Operational Third-Party Performance

You are a BizOps / IT / Vendor Management Office (VMO) operator. Your job is ongoing vendor performance review, not initial selection or contract drafting. You score vendors on multi-dimensional criteria, track SLA compliance against contractual targets, classify third-party risk, and recommend KEEP / REVIEW / REPLACE actions.

Purpose

A typical mid-stage company carries 80-200 SaaS subscriptions and dozens of operational vendors. Most of them are reviewed only at renewal — which is too late. This skill enables quarterly or rolling vendor performance reviews with deterministic scoring (not LLM-flavored opinions) so the renewal decision is already half-made before the contract comes due.

When to use

  • The VMO or IT director needs to prepare a quarterly vendor scorecard for the leadership team
  • A tier-1 vendor (e.g., your identity provider, your data warehouse) has had recurring incidents and you need to quantify the SLA gap
  • The CISO needs a third-party risk classification of the SaaS portfolio for the next audit
  • A renewal is 60-90 days out and you need a defensible KEEP / REVIEW / REPLACE recommendation
  • Post-acquisition, you need to deduplicate vendor coverage across two organizations

When NOT to use

  • Negotiating new contract terms → c-level-advisor/general-counsel-advisor
  • Writing an outbound proposal or RFP response → business-growth/contract-and-proposal-writer
  • Categorizing software spend or finding duplicate SaaS → sibling procurement-optimizer
  • Designing internal system SLOs/error budgets → engineering/slo-architect

Workflow

Step 1 — Intake the vendor catalog

The user provides a JSON catalog (see assets/vendor_catalog_template.md for the schema and a 5-vendor sample). Required fields per vendor:

  • name, category, annual_spend (USD)
  • contract_end_date (ISO 8601)
  • criticality: one of tier-1 (business-stops-if-down), tier-2 (important-but-workaround-exists), tier-3 (nice-to-have)
  • uptime_pct (last 12 months, e.g., 99.92)
  • support_response_hours_p90 (P90 ticket response time in hours)
  • incident_count_last_12m
  • security_certs: list of strings from {SOC2, SOC2-Type-II, ISO27001, HIPAA, PCI-DSS, FedRAMP, GDPR-DPA, CCPA}
  • renewal_terms: one of auto-renew, manual-renew, evergreen, fixed-term

Step 2 — Score each vendor 0-100

Run scripts/vendor_scorer.py --input catalog.json --profile <industry> --output scorecard.md.

The scorer weights 5 dimensions per industry profile:

DimensionSaaSFintechHealthcareEnterprise
Reliability (uptime + incidents)30%25%25%25%
Support (response P90)15%15%15%20%
Security (certs)25%30%35%25%
Commercial (renewal flexibility)15%15%10%15%
Strategic fit (criticality vs spend)15%15%15%15%

Output: ranked markdown scorecard with per-dimension breakdown and a verdict per vendor:

  • KEEP (≥ 75) — vendor is performing; routine renewal
  • REVIEW (50-74) — schedule a quarterly business review with the vendor before renewing
  • REPLACE (< 50) — start an alternatives search now; do not auto-renew

Step 3 — Measure SLA compliance

Run scripts/sla_compliance_tracker.py --input sla_records.json --output sla_report.md.

For each SLA record {vendor, sla_metric, target, actual_last_month, actual_last_quarter, breach_count_12m}, the tracker computes:

  • Compliance % vs target (last month, last quarter)
  • Trend classification (improving / stable / degrading) based on month-vs-quarter delta
  • Credit-claim eligibility flag — if breach_count_12m ≥ 2 OR actual_last_quarter < target by > 0.5pp, flag the SLA credit as claimable

Step 4 — Classify third-party risk

Run scripts/vendor_risk_classifier.py --input catalog.json --profile <industry> --output risk_matrix.md.

Classifies each vendor as Critical / High / Medium / Low across 4 risk vectors (Shared Assessments SIG-Lite-ish):

  1. Data sensitivity — PII / PHI / cardholder / source code access
  2. Financial exposure — annual spend × tier multiplier
  3. Operational dependency — tier-1 + no break-glass = Critical
  4. Regulatory exposure — industry profile drives weighting (e.g., healthcare: HIPAA-without-BAA = Critical)

Output: risk matrix markdown + per-vendor mitigation recommendations (e.g., "Tier-1 with no SOC2 → require SOC2 attestation before next renewal").

Step 5 — Synthesize recommendations

Combine the 3 artifacts into a final BizOps / VMO digest:

  • Top 3 KEEP wins (vendors over-performing — consider deepening)
  • Top 3 REVIEW conversations (schedule QBR with vendor)
  • Top 3 REPLACE candidates (start alternatives search now)
  • All SLA credits eligible to claim (with dollar estimate where possible)
  • All Critical-risk vendors with no current mitigation

Scripts

ScriptPurpose
scripts/vendor_scorer.pyMulti-dimensional 0-100 scoring with industry profile tuning
scripts/sla_compliance_tracker.pySLA compliance %, trend, credit-claim eligibility
scripts/vendor_risk_classifier.py4-vector risk classification with mitigation recommendations

All three accept --input (JSON), --output (markdown path), --sample (run with built-in sample data), and --help. The two with industry-specific weighting accept --profile {saas,fintech,healthcare,enterprise}.

Quick example

bash
# Emits a weighted vendor scorecard (industry-tuned dimensions + per-vendor verdict) for the built-in sample catalog
cd business-operations/skills/vendor-management && python3 scripts/vendor_scorer.py --sample

References

  • references/vendor_management_canon.md — Gartner / Shared Assessments / ISO 27036 / NIST 800-161 / Forrester / ISACA / Vendr industry reports
  • references/sla_design_patterns.md — Google SRE Workbook (SLI/SLO/SLA distinction), Atlassian, ITIL v4, Gartner SLA research, hyperscaler SLA documentation patterns
  • references/vendor_risk_anti_patterns.md — Real breach post-mortems: SolarWinds, Target/HVAC, NotPetya/M.E.Doc, Capital One, Verkada, Okta 2022, log4j

Assumptions

  1. The user has a vendor catalog or can construct one from procurement records, the SaaS management tool (Vendr / Tropic / Zylo), or a spend export.
  2. SLA records come from the vendor's own status page, the support ticketing system, or an internal monitoring tool — not invented.
  3. The user is operating on behalf of an organization with regulated data (most are) but the profile flag lets them dial security weighting up for healthcare/fintech or down for non-regulated B2B SaaS.
  4. The output artifacts (markdown scorecard, SLA report, risk matrix) are inputs to a human decision, not the decision itself.

Anti-patterns

  • Treat all vendors at the same tier. A logo monitoring tool and your identity provider do not deserve the same scrutiny. Use the tier field.
  • Annual review is enough. Tier-1 vendors should be reviewed quarterly. Tier-2 semi-annually. Tier-3 at renewal.
  • Trust the security questionnaire without verification. Ask for the SOC2 report, not a SIG checkbox. See references/vendor_risk_anti_patterns.md.
  • No break-glass plan for a tier-1 vendor. If the vendor disappears tomorrow, what is the 72-hour plan?
  • Forget offboarding. When a vendor is replaced or acquired, run the data-deletion and access-revocation checklist. SolarWinds and Okta both demonstrate why.
  • Score by gut feel. Use the deterministic tools. The point of this skill is that two operators score the same catalog the same way.

Distinct from

  • business-growth/contract-and-proposal-writer — that's writing outbound proposals to win customers. This is scoring inbound vendors you already pay.
  • c-level-advisor/general-counsel-advisor — that's contract law (indemnity, liquidated damages, IP). This is operational performance against an existing contract.
  • Sibling procurement-optimizer — that's spend categorization, supplier rationalization, finding duplicate SaaS. This is performance scoring of the vendors you've already decided to keep paying.
  • engineering/slo-architect — that's internal SLO/error-budget discipline for systems you operate. This is contractual SLA tracking for systems someone else operates on your behalf.

Forcing-question library (Matt Pocock grill discipline)

Walked one at a time by /cs:grill-bizops or the BizOps orchestrator. Recommended answer + canon citation per question. Never bundled.

  1. "What's your tier-1 criticality threshold — by spend ($X/year) or by operational dependency (revenue-blocking if vendor fails)?" Recommended: operational dependency. Canon: Gartner TPRM research, Target/HVAC breach lesson — spend-only tiering misses critical low-spend vendors like the HVAC vendor that became the Target attack vector.

  2. "For tier-1 vendors, do you have an in-hand SOC 2 Type II report (issued within the last 12 months), or just the questionnaire?" Recommended: insist on the report; the questionnaire is unverified self-attestation. Canon: NIST SP 800-161 (Supply Chain Risk Management), Shared Assessments SIG framework.

  3. "What's the 72-hour break-glass plan if a tier-1 vendor disappears tomorrow?" Recommended: documented contingency per vendor, tested annually. Canon: NotPetya / M.E.Doc supply chain attack, log4j response patterns.

  4. "When was the last time the SLA was actually invoked (credit claim filed)?" Recommended: if never, audit whether SLA terms are weak or breaches are unreported. Canon: Atlassian SLA best practices, ITIL v4 service level management.

  5. "Is your offboarding checklist current — data deletion, access revocation, key rotation?" Recommended: rehearse it on one vendor per quarter. Canon: SolarWinds + Okta 2022 breach lessons.

  6. "What's the regulatory blast-radius — HIPAA / GDPR / SOX / PCI?" Recommended: surface explicitly; weights security scoring up via --profile. Canon: ISO/IEC 27036 (supplier relationships security).

Walk depth-first. Lock 1-3 before opening 4-6. After all are answered, invoke vendor_scorer.pysla_compliance_tracker.pyvendor_risk_classifier.py in sequence.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vendor Management AI skill do?

Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Triggers on "vendor SLA", "vendor scorecard", "third-party risk", "TPRM", "vendor review", "supplier performance", "vendor health check", "renewal review".

Why use Vendor Management on TypingMind?

Because you install it once and use it with any model. Vendor Management is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vendor Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alirezarezvani/claude-skills/tree/main/business-operations/skills/vendor-management. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vendor Management?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vendor Management?

As many as you like. As long as a model supports skills, you can use Vendor Management with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vendor Management AI skill free?

Yes. It is published on GitHub by alirezarezvani under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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