revelata

name	revelata
description	Broad orchestrator for Revelata deepKPI research on US public companies — use for complex multi-step queries that cross multiple workflows (KPIs + filing text + segments, pressure-test plus follow-up data pulls, peer benchmarks plus seasonality, etc.). Routes to narrow skills (kpi, company-summary, filing, seasonality, implied-metric, pressure-test, benchmark, ideas) when a single workflow fits. Pulls SEC metrics (10-K/10-Q/8-K): segments, unit KPIs (stores, comps, ARPU, users), statements, cash flow; filing markdown and verbatim quotes; implied Q4/per-unit, seasonality, Excel. For "pull data", historicals, "find the KPI", seasonality, .xlsx, filing excerpts, pressure-test analyst PDFs, peer benchmarks, idea generation, or company summaries across multiple needs.
version	1.0.0
homepage	https://www.revelata.com
metadata	{"openclaw":{"emoji":"📊","requires":{"env":["DEEPKPI_API_KEY"],"bins":["curl"]},"primaryEnv":"DEEPKPI_API_KEY"}}

Revelata deepKPI orchestrator

Query structured KPIs, SEC filing text, and company summaries for US public companies, powered by Revelata.

This is the broad orchestrator for the Revelata bundle. Use it when a request crosses multiple workflows. For a single, well-scoped task, route to the narrow skill below.

Data access

See ../_common/data-source-rules.md — single source of truth for how to call deepKPI from MCP-capable runtimes (Claude, ChatGPT) vs non-MCP runtimes (OpenClaw). Every skill below depends on this.

Hard stop on connection failures

See ../_common/connection-failure.md. If deepKPI access fails, STOP and ask the user before falling back to other sources. This rule applies to every skill in the bundle.

Sub-skill routing

Read the relevant narrow skill before doing any work. Multiple skills may apply to a single request — chain through all that fit.

User need	Skill
No specific company or thesis — "what should I invest in?", "what stock should I buy?", new ideas, interesting companies, boredom / open exploration	ideas — interactive funnel + company_summary_search screen; then kpi for deep pulls
Pull historical KPIs / financials from deepKPI	kpi
What a company does, segments / geographies, or thematic "who does X?" lists	company-summary — named company: get_company_summary / get_company_segments; discovery: company_summary_search then hydrate as needed
Pull full filing markdown into chat, verbatim SEC text, quotes, MD&A / risk-factor language, or "what did they say"	filing — before any web/SEC.gov: list_sec_filing_markdowns (free) → get_sec_filing_markdown (10 credits). Return full markdown when they want the document; blockquoted excerpts for quote-style asks; no paraphrase as quotes
Derive missing Q4 numbers, a segment remainder, or per-unit economics (ASP, ARPU, AUV, take rate)	implied-metric
Split annual forecasts into quarterly estimates / seasonality patterns	seasonality
Produce an Excel workbook (.xlsx) from deepKPI data	Whichever data skill applies (kpi, seasonality, etc.); then follow ../_common/revelata-excel-styling-rules.md
Pressure-test a sell-side / analyst report against SEC filing data (HTML report, Chart.js, provenance links)	pressure-test
Peers / comps, benchmark a company, most similar public companies, or operational comp sets	benchmark — always read the kpi skill first for KPI mechanics

Default entry points by intent:

• For metrics and modeling feeds, start with kpi (it chains to implied-metric, seasonality, and ../_common/revelata-excel-styling-rules.md as needed).
• For business description, segment structure, or thematic company lists, start with company-summary.
• For filing markdown (full or excerpts) and verbatim quotes, start with filing.

If a request mixes these, run every narrow skill that applies.

Sub-skill summary

kpi — Primary workflow for structured KPIs (company ID, list_kpis / search_kpis, gap handling including Q4 derivation), provenance rules, in-chat tables, and the mandatory post-pull Excel offer.

company-summary — get_company_summary (what they do) and get_company_segments (how they break out segments / geos); company_summary_search for thematic "who does X?" discovery. Not for KPI time series.

filing — SEC filing markdown in chat: full filing or excerpts, verbatim quotes, MD&A / risk language. Tools: list_sec_filing_markdowns → get_sec_filing_markdown, source hierarchy (tool-first, not web), blockquote discipline for quote-style asks. Distinct purpose from KPI time series.

implied-metric — Compute metrics that deepKPI doesn't report directly from data that IS reported: Q4 = FY − (Q1+Q2+Q3), missing segment = total − known segments, per-unit economics (revenue per store, ARPU, ASP), take rates, penetration rates, geographic mix percentages. Standalone so custom user-built skills can invoke it.

seasonality — Compute each quarter's typical share of the full fiscal year from 2–3 years of actuals, then apply those ratios to split an annual projection into quarterly estimates.

pressure-test — End-to-end workflow for uploaded analyst PDFs: extract 4–6 claims, pull granular deepKPI metrics per claim, build paired "supports" / "complicates" evidence with mandatory provenance hyperlinks, and emit a Revelata-branded interactive HTML report (references/html-template.md, references/chart-patterns.md). After the draft HTML exists, run the mandatory internal draft HTML QA rubric (references/double-check.md), then revise and re-check as needed before presenting the file. Always read kpi for KPI mechanics; use filing when the test needs verbatim filing passages; use company-summary for business description / segment structure / thematic lists when useful; use implied-metric when filling Q4 or segment gaps.

benchmark — Curated operational benchmark sets (not trading multiples): company_summary_search for candidates, KPI fingerprint + alignment, diff-driven segment sub-benchmarks, chat 1-pager, optional HTML (references/html-template.md), Excel via ../_common/revelata-excel-styling-rules.md. Always read kpi first.

ideas — Onramp when the user has no ticker and no thesis: rapid interview (multiple-choice by default), company_summary_search for a 10–15 name screen with thesis-matched KPIs, then deep pulls on 1–2 chosen names per kpi. references/sector-kpi-map.md for diagnostic KPI concepts. No default Excel offer. Not for users who already named a company or a specific metric — use kpi instead.