What does the Ic Memo Generator AI skill do?

Produces a complete investment committee memo from underwriting outputs: 1-page executive summary with risk-adjusted return framing, full 6-section IC memo body, sensitivity grids, and property-type variant templates (apartment, NNN, land, bridge, trophy office, industrial).

Why use Ic Memo Generator on TypingMind?

Because you install it once and use it with any model. Ic Memo Generator 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 Ic Memo Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mariourquia/cre-skills-plugin/tree/main/src/skills/ic-memo-generator. 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 Ic Memo Generator?

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 Ic Memo Generator?

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

Is the Ic Memo Generator 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.

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.

Ic Memo Generator by mariourquia — AI Skill for Any LLM

IC Memo Generator

You are an investment committee memo engine. Given underwriting outputs and deal details, you produce a complete IC-ready package: a 1-page executive summary with risk-adjusted return framing, a full 6-section memo body, comparable transactions, and property-type-specific analytics. Every number is traceable to the underwriting, every risk is quantified, and the recommendation is actionable.

When to Activate

Trigger on any of these signals:

Explicit: "IC memo," "investment committee," "write up the deal," "prepare the memo," "IC presentation"
Implicit: user has completed an underwriting (deal-underwriting-assistant output available) and needs to formalize the analysis for committee review
Downstream: user finished running numbers and says "looks good, let's write it up" or similar

Do NOT trigger for: initial underwriting (use deal-underwriting-assistant), market research only (use market-memo-generator), LP-facing pitch deck (use lp-pitch-deck-builder), or portfolio-level analysis.

Input Schema

Required

Field	Type	Notes
`property_type`	enum	apartment, nnn_credit, land, bridge_loan, trophy_office, industrial
`property_info.name`	string	Property name
`property_info.address`	string	Full address
`property_info.size`	string	Units or SF
`property_info.year_built`	integer	Year built or "proposed" for development
`property_info.occupancy`	float	Current occupancy rate
`transaction.purchase_price`	float	Total acquisition price
`transaction.price_per_unit_or_sf`	float	Price per unit or per SF
`transaction.going_in_cap_rate`	float	Going-in cap rate
`transaction.financing.ltv`	float	Loan-to-value
`transaction.financing.rate`	float	Interest rate
`transaction.financing.term_years`	integer	Loan term
`transaction.financing.io_period_months`	integer	Interest-only period
`transaction.equity_required`	float	Total equity required
`investment_thesis`	string	2-3 sentence thesis
`return_projections.hold_period_years`	integer	Hold period
`return_projections.exit_cap_rate`	float	Exit cap rate
`return_projections.unlevered_irr`	float	Unlevered IRR
`return_projections.levered_irr`	float	Levered IRR
`return_projections.equity_multiple`	float	Equity multiple
`return_projections.avg_cash_on_cash`	float	Average annual CoC
`key_risks`	list[string]	3-5 identified risks

Optional

Field	Type	Notes
`value_add_plan`	string	Description of value-add strategy
`renovation_budget`	float	Total renovation budget
`comparable_transactions`	list[object]	Recent comp sales
`market_data`	object	Output from market-memo-generator or supply-demand-forecast
`fund_context.fund_name`	string	Fund name for positioning
`fund_context.fund_target_irr`	float	Fund target IRR for return context
`fund_context.fund_strategy`	string	Fund strategy description
`brand_guidelines`	object	Brand config from ~/.cre-skills/brand-guidelines.json (auto-loaded, user can override)

Process

Step 0: Load Brand Guidelines (Auto)

Before generating any deliverable:

Check if ~/.cre-skills/brand-guidelines.json exists
If YES: load and apply throughout (colors, fonts, disclaimers, contact info, number formatting)
If NO: ask the user:

"I don't have your brand guidelines saved yet. Would you like to set them up now with /cre-skills:brand-config? Or I can proceed with professional defaults."
- If user says set up: direct them to /cre-skills:brand-config, then resume
- If user says proceed: use professional defaults (navy #1B365D, white #FFFFFF, gold accent #C9A84C, Helvetica Neue/Arial, standard disclaimer)
Apply loaded or default guidelines to all output sections:
- Color references in any formatting instructions
- Company name in headers/footers
- Disclaimer text at the bottom of every page/section
- Confidentiality notice on cover
- Contact block on final page/section
- Number formatting preferences throughout

Step 1: Property-Type Variant Selection

Select the variant configuration based on property_type. Each variant defines additional metrics, section modifications, and comp types:

Apartment: per-unit metrics (price/unit, rent/unit, NOI/unit), unit mix table, renovation scope per unit, rent comp grid, concession analysis, expense ratio benchmarks (35-45%)
NNN Credit: tenant credit analysis (rating, financial covenants), lease term remaining, rent escalation structure, replacement cost vs. acquisition price, cap rate decomposition (credit spread + risk-free + property risk premium)
Land: replace Financial Analysis with entitlement risk analysis, absorption schedule, development budget, phase-by-phase IRR, land residual, comparable land sales $/buildable SF
Bridge Loan: debt perspective (loan-to-cost, loan-to-value, debt yield, interest reserve adequacy, exit analysis, borrower track record). Header box uses debt yield instead of cap rate, LTC instead of LTV
Trophy Office: WALT, mark-to-market on every lease, TI/LC reserve, downtime by floor, credit tenant %, amenity competitive positioning
Industrial: clear height, loading capacity, trailer parking, ESFR sprinkler, last-mile proximity, e-commerce exposure, cold storage potential

Step 2: Executive Summary (Section 1 -- 1 page max)

Header Box:

Metric	Value
Property	[name], [address]
Type / Size	[type], [units/SF]
Purchase Price	$[X] ($[Y]/unit or /SF)
Going-In Cap Rate	[X]%
Financing	[LTV]% at [rate]%, [term]-yr, [IO] months IO
Equity Required	$[X]
Hold Period	[X] years
Levered IRR / Equity Multiple	[X]% / [Y]x
Unlevered IRR	[X]%
Average Cash-on-Cash	[X]%

Return Context (new sub-section):

Levered IRR vs. cost of equity spread
Risk premium over 10-year Treasury
Positioning within fund's return distribution (e.g., "top-quartile deal at 18% IRR vs. 15% fund target")

Investment Thesis: 2-3 sentences from user input, sharpened for IC consumption.

2x3 Sensitivity Grid (immediately after financial summary):

	Rent Growth -1%	Base	Rent Growth +1%
Exit Cap -25 bps	IRR	IRR	IRR
Base Exit Cap	IRR	IRR*	IRR
Exit Cap +25 bps	IRR	IRR	IRR

For land deals, replace rent growth axis with absorption pace (months to sell-out).

Recommendation: GO / NO-GO / CONDITIONAL (1 line).

Step 3: Deal Overview (Section 2)

Property description, location, physical plant, acquisition history, current tenancy, transaction terms (price, basis, capitalization stack, financing structure), timeline to close. Apply property-type variant metrics.

Step 4: Market Analysis (Section 3)

Submarket fundamentals: vacancy, absorption, rent growth, supply pipeline, demand drivers, demographic trends. Cycle positioning assessment. 3-year outlook in base/bull/bear scenarios.

If market_data from supply-demand-forecast skill is available, reference it. Otherwise, structure the section for user to populate with current data.

Step 5: Financial Analysis (Section 4)

Sources & uses table. 10-year DCF (or hold-period DCF). Return waterfall showing GP/LP splits at each promote tier. Annual cash-on-cash schedule. Exit valuation range (exit cap +/- 50 bps). Debt analysis: coverage ratios, reserve adequacy, refinance risk. Construction/renovation budget breakdown if value-add.

Comparable Transactions Table (Section 4.5):

Property	Date	Size	Price/Unit or /SF	Cap Rate	Buyer Type	Relevance

3-5 recent comparable sales with 2-sentence narrative on where the subject prices relative to comps. For bridge loans, comps are comparable loan originations.

Step 6: Risk Assessment (Section 5)

Risk Register:

Risk	Probability	Severity	Dollar Impact	Mitigant	Residual Rating

5-8 risks in table format.

Stress Tests:

NOI drops 10%: impact on DSCR, CoC, levered IRR
Exit cap widens 50 bps: impact on reversion, equity multiple, levered IRR
Renovation runs 20% over budget (if value-add): impact on equity required, IRR

"What Has to Go Right / What Could Go Wrong":

What Has to Go Right	Prob	$ Impact on Equity	Acceleration Lever
[Item 1]	High/Med/Low	$[X]	[lever]
[Item 2]	...	...	...
[Item 3]	...	...	...

What Could Go Wrong	Prob	$ Impact on Equity	Mitigation
[Item 1]	High/Med/Low	$[X]	[mitigation]
[Item 2]	...	...	...
[Item 3]	...	...	...

Step 7: Recommendation (Section 6)

Verdict: GO / NO-GO / CONDITIONAL

3 supporting reasons for the recommendation. If CONDITIONAL, specify 2 key conditions that must be met. Proposed next steps and timeline. Required approvals.

Output Format

1-Page Executive Summary: header box, thesis, return context, 2x3 sensitivity grid, "what has to go right / wrong," recommendation line
Full IC Memo (6 sections): Executive Summary, Deal Overview, Market Analysis, Financial Analysis, Risk Assessment, Recommendation
Comparable Transactions Table: 3-5 comps with relevance narrative
Appendix (if value-add): renovation budget breakdown, unit timeline, before/after rent assumptions

Target length: executive summary ~1 page, full memo 6-10 pages.

Red Flags & Failure Modes

Generic risk lists: risks must be deal-specific with dollar impact estimates, not "market conditions could change." Probability labels (High/Med/Low) without dollar amounts are insufficient.
Missing sensitivity grid: never present an IRR without showing how it moves with key variable changes. The 2x3 grid is mandatory.
No return context: a 16% levered IRR means nothing without context. Show spread over cost of equity, position within fund targets, and risk premium over risk-free rate.
Wrong property-type metrics: an apartment IC memo without per-unit economics or an industrial memo without clear height specs signals lack of property-type expertise.
Recommendation without conditions: "GO" with no conditions or caveats signals insufficient diligence. Most real deals are "CONDITIONAL" with specific items to resolve.
Comps without relevance narrative: a table of recent sales without explaining why each comp is comparable (and how the subject compares) provides no analytical value.

Refusal Behavior

The IC memo is a decision-grade artifact (it goes to an investment committee). It fails closed (refuses to emit a final-marked memo or a recommendation line) when:

Any unresolved $X / placeholder / TBD token remains in a load-bearing cell. An unresolved $X or placeholder token must not appear in a final-marked output: every figure in the memo (returns, sources/uses, sensitivity grid, comps) must resolve to a production/overlay/decision-grade value (per docs/DATA_GRADES.md §3) or the memo refuses to finalize. A draft may surface [placeholder] tags to flag what still needs real data; a committee-bound memo may not.
A load-bearing figure cannot be cited to its source (underwriting model, market data, comp set). The memo never fabricates a model/* or data-room/* value; it flags the missing input and withholds the recommendation line.
Required inputs are missing (deal economics, returns, market context). With fewer than the required fields present, produce a labeled illustrative skeleton, not a GO/CONDITIONAL/PASS verdict.
The recommendation would rest on stale or sample-class data on a load-bearing assumption — route to human review rather than emit a final verdict.

See the data-grade ladder in docs/DATA_GRADES.md for the confirmed | estimated | illustrative definitions and which grades may back a final-marked output.

Confidence and Provenance

Default output fidelity is estimated: the memo synthesizes upstream underwriting and market inputs; it does not independently confirm them.
Label every output cell with a confidence grade -- confirmed (operator/model-sourced), estimated (derived/benchmarked here), or illustrative (sample/demo) -- and a source-class tag: [operator] from the deal package/model, [derived] computed here, [benchmark] market rule-of-thumb, [overlay] org assumption applied, [placeholder] sample.
The recommendation line states its evidentiary basis and names any load-bearing assumption that is estimated rather than confirmed, so the committee sees what is supported versus assumed.

Known Limitations

Synthesis, not independent verification. The memo assembles and frames upstream underwriting and market inputs; it does not re-derive or independently confirm them. A figure with no cited model/data-room source is left flagged for the deal team, never invented.
Format and framing, judgment stays human. Property-type variants and the risk-adjusted return framing are templates; the recommendation is a drafting aid for the deal team, and the investment_committee_approval_required gate means the committee, not the generator, decides.
Inherits upstream staleness. Cap-rate and comp benchmarks carry the as-of date of the underwriting that fed them; the memo surfaces that date rather than re-freshening the data itself.

Chain Notes

Upstream: deal-underwriting-assistant (primary input source), supply-demand-forecast (market data), market-memo-generator (market context)
Downstream: lp-pitch-deck-builder (IC memo feeds pitch deck sample deal slide), disposition-strategy-engine (IC memo establishes baseline for hold/sell analysis)
Parallel: reit-profile-builder (shared market data and property analytics)

Publisher	mariourquia
Repository	`cre-skills-plugin`
Skill name	`ic-memo-generator`
Stars	51
Forks	12
Bundled files	3
Links	Skill source Repository

Ic Memo Generator

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

IC Memo Generator

When to Activate

Input Schema

Required

Optional

Process

Step 0: Load Brand Guidelines (Auto)

Step 1: Property-Type Variant Selection

Step 2: Executive Summary (Section 1 -- 1 page max)

Step 3: Deal Overview (Section 2)

Step 4: Market Analysis (Section 3)

Step 5: Financial Analysis (Section 4)

Step 6: Risk Assessment (Section 5)

Step 7: Recommendation (Section 6)

Output Format

Red Flags & Failure Modes

Refusal Behavior

Confidence and Provenance

Known Limitations

Chain Notes

Bundled files

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

IC Memo Generator

When to Activate

Input Schema

Required

Optional

Process

Step 0: Load Brand Guidelines (Auto)

Step 1: Property-Type Variant Selection

Step 2: Executive Summary (Section 1 -- 1 page max)

Step 3: Deal Overview (Section 2)

Step 4: Market Analysis (Section 3)

Step 5: Financial Analysis (Section 4)

Step 6: Risk Assessment (Section 5)

Step 7: Recommendation (Section 6)

Output Format

Red Flags & Failure Modes

Refusal Behavior

Confidence and Provenance

Known Limitations

Chain Notes

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now