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what-if

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

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包含的文件(5)

  • SKILL.md6.0 KB
  • references/knowledge-frameworks.md667 B
  • references/methodology.md1.0 KB
  • references/modes.md707 B
  • references/output-structure.md671 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

ParameterDefault ValueRationale
ticker(required)Stock symbol to analyze
lookback_quarters4Standard 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.

Output File

Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_what-if_{affix}.md .

Output Structure

  1. Executive Summary (≤200 words) — headline conclusions for the analysis.
  2. Data Sources — filings + structured endpoints used, with {ticker} {citation_id} page<N> citations.
  3. Analysis — the core findings, tables, and commentary for this dimension.
  4. Key Metrics — the quantitative results with QoQ/YoY context where relevant.
  5. Coverage Gaps & Citations — data not retrievable + citation index.

Citations & memory: follow contracts/citation-and-memory.md — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link; a bottom Citations section provides a non-duplicative roll-up index; the closing TUI reply includes a compact Key Citations list (headline 5–10 facts) of clickable /v/ URLs; and append the run to agentii.md per contracts/agentii-md-schema.md.

Preflight

Run canonical pre-flight per contracts/preflight.md.

Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

Memory & Snapshot

  • Memory load (pre-flight): load prior workspace context for the ticker before retrieval — see contracts/memory-load.md.
  • Structured output frontmatter: emit the FR-090 block (key_metrics, conclusions, facts_count, deducted_count, views_count, citation_count) per contracts/output-frontmatter-schema.md.
  • Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as [FACT]/[DEDUCTED]/[VIEW] — see contracts/snapshot-synthesis.md.
  • Session archival: record the run under sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.

Final Summary (TUI)

End the closing chat reply with a compact Key Citations list (headline 5–10 facts), each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link, so the user can cmd+click straight to the exact SEC page. See contracts/citation-and-memory.md.

Error Handling

ErrorAction
Ticker not foundSuggest checking spelling or trying list_coverage
No data availableFlag in Coverage Gaps, proceed with available data
API key invalidDirect user to agentii.ai/api-keys
MCP server unreachableRetry once; if persistent, halt with AGENTII_MCP_UNREACHABLE

References

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