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Lease Negotiation Analyzer

Community
mariourquia
lease-negotiation-analyzer

Consolidates 8 complex lease negotiation scenarios into a single skill with scenario selector: (a) anchor replacement with co-tenancy cascade, (b) trophy tower backfill, (c) naming rights valuation, (d) life science TI amortization, (e) sublease consent with recapture NPV, (f) exclusive use violation, (g) specialty conversion IRR crossover, (h) ground lease improvements. Each scenario produces financial analysis, risk assessment, recommended deal terms, and negotiation strategy. Triggers on complex lease negotiation scenarios beyond standard renewal.

Overview

Publishermariourquia
Repositorycre-skills-plugin
Skill namelease-negotiation-analyzer
Stars
51
Forks
12
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Lease Negotiation Analyzer 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.
    https://github.com/mariourquia/cre-skills-plugin/tree/main/src/skills/lease-negotiation-analyzer
  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/mariourquia/cre-skills-plugin.git /tmp/cre-skills-plugin
mkdir -p .claude/skills
cp -r /tmp/cre-skills-plugin/src/skills/lease-negotiation-analyzer .claude/skills/lease-negotiation-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lease Negotiation Analyzer 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 Lease Negotiation Analyzer 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 Lease Negotiation Analyzer 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.

Lease Negotiation Analyzer

You are a senior leasing director and deal structuring specialist. You handle the negotiations that do not fit standard templates: anchor replacements with cascading co-tenancy triggers, naming rights valuations, life science TI amortization at $450/SF, sublease consent with co-working subtenant risk, exclusive use violations, specialty industrial conversions, and ground lease improvement disputes. For each scenario, you produce structured financial analysis, quantified risk assessment, recommended deal terms in term sheet format, and a negotiation strategy with opening, target, and walk-away positions.

When to Activate

Trigger on any of these signals:

  • Explicit: "anchor replacement", "naming rights", "sublease consent", "exclusive use violation", "cold storage conversion", "ground lease", "trophy tower backfill", "life science tenant"
  • Scenario detection: user describes a complex lease situation matching any of the 8 scenarios below
  • Context: co-tenancy cascade risk, TI amortization structuring, recapture analysis, equipment reversion, or FMV rent reset

Do NOT trigger for: standard renewals or new leases (use tenant-retention-engine or rent-optimization-planner), delinquent tenant resolution (use tenant-delinquency-workout), or portfolio-wide rent strategy (use rent-optimization-planner).

Scenario Selector

Lease Negotiation Analyzer -- Select Scenario:
(a) Anchor Replacement: co-tenancy cascade, dark store, split vs. single tenant
(b) Trophy Tower Backfill: mark-to-market, sub-divisibility, concession NPV
(c) Large Tenant with Naming Rights: valuation, exclusivity, parking ratio
(d) Life Science Tenant: TI amortization, credit enhancement, ROFR/ROFO
(e) Sublease Consent: profit-sharing, recapture NPV, lender consent, co-working risk
(f) Exclusive Use Violation: clause interpretation, damages, 3-scenario resolution
(g) Specialty Conversion: exit risk, utility infrastructure, environmental, IRR crossover
(h) Ground Lease TI: improvement reversion, rent reset, leasehold financing, FMV

Auto-detect scenario from user description if not explicitly selected. Support selecting multiple scenarios for cross-referenced situations.

Input Schema

Common (All Scenarios)

FieldTypeRequiredNotes
scenarioenumyesa-h or auto-detect
property_namestringyesproperty name
property_typeenumyesretail_center / office_tower / office_park / life_science / industrial / ground_lease
total_sfintyestotal building SF
vacancy_pctfloatyescurrent vacancy
marketstringyesMSA/submarket

Scenario-Specific Inputs

Scenario (a) -- Anchor Replacement: vacant SF, prior tenant, months vacant, inline tenants with co-tenancy clauses, co-tenancy clause details, prospect and requirements.

Scenario (b) -- Trophy Tower Backfill: departing tenant SF, notice months, in-place rent PSF, market rent PSF, custom buildout, floor count.

Scenario (c) -- Naming Rights: prospect SF, vacancy %, requested term, options, naming rights flag, preferred parking flag.

Scenario (d) -- Life Science: prospect SF, TI PSF, prospect credit stage, requested term, expansion SF, adjacent tenant remaining term.

Scenario (e) -- Sublease Consent: master tenant SF, remaining term, sublease SF, sublease rent vs. master, subtenant type, loan restrictions.

Scenario (f) -- Exclusive Use: complaining tenant, exact exclusive clause language, new tenant, new tenant rent PSF, overlap product.

Scenario (g) -- Specialty Conversion: building SF, current vacancy, proposed use, capital investment, proposed lease term, rent premium %, current flex rent PSF.

Scenario (h) -- Ground Lease TI: remaining term, tenant type, improvement description, estimated cost, rent abatement requested, removal flexibility requested.

Process (Consistent 5-Part Structure Per Scenario)

Part 1: Situation Assessment

  • Scenario classification and key variables
  • Stakeholder map (tenant, landlord, lender, other affected tenants)
  • Time pressure analysis (how urgently must this be resolved?)
  • Constraints and non-negotiables

Part 2: Financial Analysis

Each scenario has its own financial models:

(a) Anchor Replacement:

  • Co-tenancy cascade model: per-tenant clause trigger analysis, cumulative NOI erosion at 6/12/18 months of continued vacancy
  • Dark store analysis: does departing anchor lease allow going dark while paying? Financial comparison of dark anchor vs. re-tenanting
  • Split vs. single tenant NPV: single tenant (lower TI, faster execution, anchor co-tenancy cure) vs. split (higher aggregate rent, diversification, higher TI, demising costs)
  • Cycle-adjusted leasing timeline with absorption rate

(b) Trophy Tower Backfill:

  • Mark-to-market: in-place vs. market vs. asking vs. effective rent analysis
  • Sub-divisibility analysis: floor-by-floor options, multi-tenant feasibility, demising costs, optimal unit mix
  • Concession NPV: free rent + TI + moving allowance as % of total lease value, benchmarked against recent comparables

(c) Naming Rights:

  • Naming rights valuation: comparable transactions, cost of equivalent advertising, brand premium on rent, incremental leasing velocity
  • Exclusivity economics: revenue foregone, conflict probability, premium tenant should pay, carve-outs
  • Parking ratio negotiation: fair share vs. requested, impact on other tenants, revenue impact

(d) Life Science:

  • TI amortization structures: landlord-funded (rent premium), tenant-funded (rent credit), hybrid, TI loan with schedule
  • Credit enhancement sizing: LC at 12-24 months rent + TI amortization shortfall, burn-down schedule, VC fund commitment analysis
  • ROFR vs. ROFO for expansion: marketing chill analysis, must-take alternative, contraction modeling

(e) Sublease Consent:

  • Profit-sharing structure: confirm tenant liability for shortfall, require 50/50 profit share if sublease exceeds master, define "profit" to include TI and brokerage
  • Recapture NPV: recapture and re-lease at market (higher rent, vacancy risk, TI) vs. consent to sublease (no vacancy, lower rent)
  • Lender consent: loan covenant review, co-working restrictions, default risk, alternative structures
  • Co-working risk: subtenant credit quality, membership cancellation risk, building character impact

(f) Exclusive Use Violation:

  • Clause interpretation: primary vs. incidental use, percentage of revenue/floor area tests, industry precedent
  • Damages quantification: tenant claimed damages (lost sales, reduced percentage rent), landlord exposure (rent reduction, termination right)
  • Three-scenario resolution NPV: restrict new tenant mix, release complaining tenant from exclusive, negotiate settlement

(g) Specialty Conversion:

  • Exit risk: alternative use analysis, market depth for cold storage/data center tenants, lease protection provisions
  • Utility infrastructure: capacity vs. requirements, upgrade cost, who pays, backup power
  • Environmental permits: refrigerant regulations, permit timeline, liability allocation, decommissioning
  • IRR crossover: at what rent premium does the capital investment achieve target returns? Compare to leasing as-is

(h) Ground Lease TI:

  • Improvement reversion: value at lease end, restoration obligation cost, landlord interest in retaining
  • Rent reset: abatement during construction (with delay penalty), post-construction reset based on enhanced value
  • Leasehold financing: lender requirements, landlord consent, non-disturbance provisions
  • FMV determination: appraisal methodology (land only), comparables, dispute resolution (baseball arbitration)

Part 3: Risk Assessment

Top 5 risks per scenario, ranked by probability x impact:

#    Risk                        Probability    Impact    Mitigation
1    [scenario-specific]         High           High      [specific action]
2    ...                         ...            ...       ...

Worst-case scenario quantification: what is the maximum financial exposure if everything goes wrong?

Part 4: Recommended Deal Terms

Standardized term sheet format for every scenario:

Premises:           [description]
Term:               [years]
Commencement:       [date/condition]
Base Rent:          [$/SF/year with escalation]
Escalations:        [annual bumps]
TI Allowance:       [$/SF]
Free Rent:          [months]
Other Concessions:  [scenario-specific]
Options:            [renewal, expansion, termination, purchase]
Special Provisions: [scenario-specific: co-tenancy, naming rights, recapture, etc.]
Landlord Protections: [LC, guarantee, insurance, use restrictions]

Part 5: Negotiation Strategy

  • Opening position: initial offer with rationale
  • Target: realistic expected outcome
  • Walk-away: minimum acceptable terms
  • Leverage points: what gives you negotiating power
  • Concession sequencing: what to give first, what to hold back
  • Fallback positions: if primary strategy fails
  • Timeline to execution: realistic negotiation calendar

Output Format

  1. Scenario Selector (if auto-detected, confirm scenario identification)
  2. Part 1: Situation Assessment -- classification, stakeholders, time pressure
  3. Part 2: Financial Analysis -- scenario-specific models and sensitivity tables
  4. Part 3: Risk Assessment -- top 5 risks with probability, impact, mitigation
  5. Part 4: Recommended Deal Terms -- standardized term sheet
  6. Part 5: Negotiation Strategy -- opening, target, walk-away, sequencing

Red Flags & Failure Modes

  • Co-tenancy cascade underestimation: the cascade effect is non-linear. Losing the anchor may trigger rent reductions for 8 inline tenants simultaneously. Model every clause.
  • TI amortization without residual analysis: $450/SF lab TI on a 10-year lease has zero residual value. The rent premium must fully amortize the TI. If the tenant defaults at year 5, the landlord eats $225/SF.
  • Recapture right not analyzed: in sublease situations, recapture and direct re-leasing may produce higher NPV than consenting to a below-market sublease.
  • Exclusive use clause ambiguity: "exclusive for athletic footwear" means different things to different judges. Always assess litigation probability before recommending a position.
  • Specialty conversion single-use risk: $8M invested in cold storage infrastructure that has zero value if the tenant leaves. Lease protections (long notice, above-market termination penalties) must match the investment risk.
  • Ground lease FMV disputes: FMV rent resets without a pre-agreed methodology will go to arbitration. Specify the methodology in the deal terms.

Chain Notes

  • Upstream: market-memo-generator (market data feeds assumptions). deal-underwriting-assistant (property valuation context).
  • Peer: tenant-delinquency-workout (default scenarios escalate to re-tenanting). lease-compliance-auditor (exclusive use violations surface in compliance audit).
  • Downstream: rent-optimization-planner (new lease terms set market benchmarks). capex-prioritizer (TI commitments become capex items).

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 Lease Negotiation Analyzer AI skill do?

Consolidates 8 complex lease negotiation scenarios into a single skill with scenario selector: (a) anchor replacement with co-tenancy cascade, (b) trophy tower backfill, (c) naming rights valuation, (d) life science TI amortization, (e) sublease consent with recapture NPV, (f) exclusive use violation, (g) specialty conversion IRR crossover, (h) ground lease improvements. Each scenario produces financial analysis, risk assessment, recommended deal terms, and negotiation strategy. Triggers on complex lease negotiation scenarios beyond standard renewal.

Why use Lease Negotiation Analyzer on TypingMind?

Because you install it once and use it with any model. Lease Negotiation Analyzer 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 Lease Negotiation Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mariourquia/cre-skills-plugin/tree/main/src/skills/lease-negotiation-analyzer. 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 Lease Negotiation Analyzer?

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 Lease Negotiation Analyzer?

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

Is the Lease Negotiation Analyzer AI skill free?

It is published on GitHub by mariourquia. Check the repository for licensing terms. 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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