Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Aznatkoiny/zAI-Skills/plugin install real-estate-investmentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/aznatkoiny/zai-skills/pro-forma)<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/pro-forma"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/pro-forma/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/pro-forma"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/pro-forma.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.01366 |
| Opus 5.5 | $0.00010 | $0.00546 |
| Sonnet 5.5 | $0.00005 | $0.00273 |
| Haiku 4.5 | $0.00002 | $0.00137 |
Grade A, and why
pro-forma scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Pro Forma Model
Requested output format (may be empty): $ARGUMENTS
Instructions
When this command is invoked, build a real estate pro forma by running the plugin's tested script — do not re-write the model from prose:
1. Collect Property Details
Use AskUserQuestion to gather (these map 1:1 to the script's input schema):
- Property type: SFR, multifamily, commercial, STR
- Purchase price
- Income: units and annual rent per unit (or a single
annual_gross_rent), other income % of rent (default 3%), vacancy rate - Operating expenses: OpEx ratio as % of EGI (benchmarks: 35-45% multifamily, 40-50% commercial, 50-60% STR)
- Financing: LTV (if the user gives a down payment %,
ltv = 1 - down_payment_pct), annual interest rate, amortization years - Assumptions: holding period (default 10), rent growth (default 3%), expense growth (default 2.5%), CapEx reserve % of EGI (default 5%), exit cap rate, selling costs % (default 3%)
2. Validate Assumptions with Market Data (optional but recommended)
If the user has a specific property address, ground the model's assumptions using the real-estate-data MCP server (tools surface as mcp__real-estate-data__<name>):
mcp__real-estate-data__estimate_rent— replace guessed rent with a Rentcast AVM estimate (requiresRENTCAST_API_KEY; free tier, 50 requests/month)mcp__real-estate-data__get_rentcast_market_data— ZIP-level vacancy rate and rent growth for the income assumptions (requiresRENTCAST_API_KEY)mcp__real-estate-data__get_attom_property— year built, building size, beds/baths for expense benchmarking (requiresATTOM_API_KEY, paid)mcp__real-estate-data__get_attom_valuation— AVM check on the purchase price (requiresATTOM_API_KEY, paid)mcp__real-estate-data__get_census_housing_stats— area median home value context (requiresCENSUS_API_KEY— the key is free to obtain)
Fallback chain: MCP tool → WebSearch for comparable data → use the user's manual inputs as-is. Note in the results which inputs are data-backed vs. assumed.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 83 lines · 24 tokens per session scan A ff71398b62fb
pro-forma is a command published in the GitHub repository Aznatkoiny/zAI-Skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 1,366 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
orchestrate
Do this task as an orchestrator. The aim is the same result at a fraction of the cost: in a long session, every token in this conversation is re-read on each later request, while a subagent's reading is discarded when it returns. The plugin's subagents run on Haiku 5.5, about 40× cheaper per token than Opus 5.5.
conjure-agent
Creates or updates a Claude Code agent definition (/.claude/agents/ .md or project-local).
conjure
Use when you want to build a new Claude Code skill, agent, hook, or MCP server but aren't sure which — or when you want to describe what you want in plain language. Auto-detects the right artifact type, asks targeted questions, explains the reasoning, then builds it.
conjure-mcp
Create a Claude Code MCP (Model Context Protocol) server. Provide a description of what external system or data source you want Claude to connect to.
conjure-help
Show help for the conjure toolkit — all commands, argument syntax, update modes, and decision guide. Use when you want to know which conjure command to use or how any conjure command works.
strip
This is the task-based stripper, not the always-on prior: a deliberate cleanup pass you asked for. Apply the fp-minify doctrine to the target and remove or compress comments that don't earn their place.