what-if

what-if is a skill for Claude Code from agentii-ai/agentii-investment-intelligence. It costs 45 tokens per session (1,442 once invoked), scanned A, a copy of revenue-decomp, Apache-2.0.

A framework for analysing financial what-if scenarios, such as base, optimistic, and pessimistic cases. It examines how changes in revenue, costs, interest rates, currencies, or commodity prices could affect results.

In plain words
What is it for?
Use it to build scenario trees, compare cases, model revenue or cost changes, and assess effects on margins or other financial measures using structured company data.
Why use it?
It helps show how sensitive a financial outlook is to uncertain assumptions instead of relying on one forecast.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the business-intelligence plugin — 4 skills, 4 commands shipped together

Good fit Use it to build scenario trees, compare cases, model revenue or cost changes, and assess effects on margins or other financial measures using structured company data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentii-ai/agentii-investment-intelligence/what-if
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add agentii-ai/agentii-investment-intelligence --skill what-if
Clone the repo
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence

Made for: Claude Code.

Or install business-intelligence, the plugin that ships this one along with the rest of its 4 skills, 4 commands.

Wrote 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.

agentmods badge for what-if

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/what-if/github.svg)](https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/what-if)
Your own site
<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/what-if"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/what-if/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.

agentmods 80×15 button for what-if

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/what-if"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/what-if.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,442 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.01442
Opus 5 $0.00023 $0.00721
Sonnet 5 $0.00009 $0.00288
Haiku 4.5 $0.00005 $0.00144

Measured 6d ago against content hash 8d2dfbccc0ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

what-if 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 6d 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.

Origin

This is a copy

88% identical to revenue-decomp — 40 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/vertical-plugins/business-intelligence/skills/agentii/what-if/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

what-if

Triggers

  • What-if scenario analysis
  • scenario tree construction
  • base bull bear case
  • sensitivity to macro variables
  • revenue scenario modeling
  • cost scenario analysis
  • margin impact scenarios
  • interest rate sensitivity
  • currency impact scenarios
  • commodity price scenarios

Defaults

Parameter Default Value Rationale
ticker (required) Stock symbol to analyze
lookback_quarters 4 Standard lookback for this skill type

Methodology

1. Retrieval Scope

This skill operates with retrieval_scope: structured_only. It performs structured data retrieval only (XBRL facts, financials, earnings calendar) — no unstructured document search. Document-retrieval tools are excluded from allowed_tools.

2. Retrieval Strategy

Follows the retrieval strategy decision tree in contracts/retrieval.md. Primary branch: (a) Structured Data Query. Resolve the canonical ticker first (exact → fuzzy alias → share-class) before any data call.

3. Temporal Scope

Default lookback: 4 fiscal quarter(s); maximum: 12. The default balances recency against the trend window this analysis requires.

4. Tool Allowlist

Per frontmatter allowed_tools:

  • search_companies — ticker resolution + company context (entity-alias fuzzy match)
  • search_xbrl_facts — primary structured financial facts (is_primary default)
  • get_company_financials — consolidated IS/BS/CF highlights
  • search_earnings_calendar — EPS actual/estimate/surprise + report dates
  • get_company_profile — sector/industry classification + metadata
  • list_xbrl_concepts — XBRL concept discovery for non-standard line items (namespace param; default us-gaap — use ifrs-full for foreign filers)

5. Protocol

  1. Pre-flight (mandatory): call get_company_fiscal_calendar/{ticker} then get_ticker_coverage/{ticker}; route on coverage.
  2. Concept discovery (non-standard concepts only): list_xbrl_concepts(query=<term>, ticker=<T>).
  3. Structured retrieval: search_xbrl_facts(ticker, concept=[...], fiscal_year=[...]) (is_primary default) and/or get_company_financials/{ticker}.
  4. Batch rule: 3+ same-tool queries → consolidate via batch_search (≤8 sub-queries).
  5. Output: write the deliverable per ## Output File, then append to agentii.md.

Read the full file on GitHub · 122 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 6d ago Changed · +3 lines 8d2dfbccc0ff
  2. 12d ago First seen · 119 lines · 45 tokens per session scan A b2f3bde89158

Subscribe to this mod's changes

what-if is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed yesterday), licensed Apache-2.0. It adds 45 tokens to every session and 1,442 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to revenue-decomp, differing in 40 lines, and is treated as a copy.

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