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.
npx skills add agentii-ai/agentii-investment-intelligence --skill what-ifgit clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligenceWrote 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/skills/agentii-ai/agentii-investment-intelligence/what-if)<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.
<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>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 | $0.00045 | $0.01442 |
| Opus 5 | $0.00023 | $0.00721 |
| Sonnet 5 | $0.00009 | $0.00288 |
| Haiku 4.5 | $0.00005 | $0.00144 |
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.
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.
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 highlightssearch_earnings_calendar— EPS actual/estimate/surprise + report datesget_company_profile— sector/industry classification + metadatalist_xbrl_concepts— XBRL concept discovery for non-standard line items (namespaceparam; defaultus-gaap— useifrs-fullfor foreign filers)
5. Protocol
- Pre-flight (mandatory): call
get_company_fiscal_calendar/{ticker}thenget_ticker_coverage/{ticker}; route on coverage. - Concept discovery (non-standard concepts only):
list_xbrl_concepts(query=<term>, ticker=<T>). - Structured retrieval:
search_xbrl_facts(ticker, concept=[...], fiscal_year=[...])(is_primary default) and/orget_company_financials/{ticker}. - Batch rule: 3+ same-tool queries → consolidate via
batch_search(≤8 sub-queries). - Output: write the deliverable per
## Output File, then append toagentii.md.
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.
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.
- 6d ago Changed · +3 lines 8d2dfbccc0ff
- 12d ago First seen · 119 lines · 45 tokens per session scan A b2f3bde89158
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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