agentsclimarketplace

Openclaw equity research

Skill X-RayLuan/awesome-ceo-stack/ceo-skill/openclaw-equity-research

An awesome, curated stack of Claude / OpenClaw agent skills for founders & CEOs — strategy, knowledge base, decks, K-12 coaching, and a full local AI promo-video pipeline. Works with Claude Code, Codex & OpenClaw.

Install
npx -y skills add X-RayLuan/awesome-ceo-stack --skill openclaw-equity-research

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when Codex needs to create, review, or update equity research work products such as earnings previews, post-earnings notes, model updates, initiating coverage, sector overviews, catalyst calendars, thesis trackers, idea generation screens, valuation memos, investor briefs, or public-company research that requires filings, transcripts, market data, spreadsheet work, citations, and analyst-review guardrails.

SKILL.md

4.8 KB, as published. Nobody here has run it

OpenClaw Equity Research

Operating Rule

Draft analyst work product for human review. Do not present output as investment, legal, tax, accounting, or trading advice. Do not claim a buy/sell/hold recommendation unless the user explicitly asks for a draft recommendation and the assumptions, valuation, risks, and sources support it.

First Pass

  1. Identify the deliverable type and audience: earnings note, preview, model update, initiation, sector overview, catalyst calendar, thesis tracker, idea screen, or one-off memo.
  2. Confirm the ticker/company, exchange, coverage universe, geography, currency, date range, and output format if missing.
  3. Use fresh sources for public-company facts, estimates, prices, filings, calendar events, executives, market data, and news. Browse when the answer depends on current information.
  4. Prefer primary sources: SEC/company filings, investor relations releases, earnings call transcripts, presentations, exchange notices, and company websites. Use reputable secondary sources only to triangulate or fill gaps.
  5. Separate fact, calculation, inference, and opinion. Label uncertainty and stale data.
  6. Produce a concise decision-ready artifact with citations, assumptions, and next checks.

Workflow Selection

  • Earnings analysis: read release, presentation, transcript, and filing; compare actuals to consensus or prior guide; isolate beats/misses, guide changes, margin drivers, cash flow, balance sheet, segment trends, and management tone.
  • Earnings preview: map consensus, guidance, buyside debate, expected KPIs, risks, and likely stock-moving questions before the print.
  • Model update: update actuals, guidance, forecast assumptions, valuation outputs, and sensitivity tables. Use spreadsheet tools for .xlsx work.
  • Initiating coverage: build company profile, industry structure, competitive position, financial history, forecast drivers, valuation, risks, catalysts, and final note/deck.
  • Morning note: summarize overnight news, earnings, rating changes, macro/sector moves, and actionable implications.
  • Sector overview: define market map, demand/supply drivers, unit economics, regulation, competitive landscape, valuation dispersion, and stock implications.
  • Thesis tracker: maintain thesis, evidence, catalysts, counterevidence, kill criteria, conviction, and unresolved questions.
  • Catalyst calendar: list dated events, expected impact, source, confidence, and prep needed.
  • Idea generation: screen for dislocations, estimate revisions, quality, momentum, valuation gaps, catalysts, short-interest, ownership changes, or variant perception.

For detailed checklists, read references/workflows.md. For quality gates and output patterns, read references/research-standard.md.

Deliverable Standard

Every research output should include:

  • Snapshot: company/ticker, date, source freshness, base currency, market data timestamp if used.
  • Key takeaways: 3-5 bullets that answer what changed, why it matters, and what to watch.
  • Evidence table: metric/event, source, reported value, comparison point, implication.
  • Model/valuation assumptions: explicit drivers, ranges, sensitivities, and what would change the conclusion.
  • Risks and counterarguments: strongest opposing case, missing data, and near-term failure modes.
  • Source list: links or file names for every material claim.
  • Human review note: checks needed before external distribution.

Tooling

  • Use web search/browsing for current filings, releases, transcripts, market data, calendars, and news.
  • Use spreadsheets when creating or editing financial models, forecast tables, comps, sensitivities, or .xlsx files.
  • Use documents when producing professional .docx notes or redlines.
  • Use presentations when producing an investment committee deck, company overview, or sector deck.
  • If a user provides local files, inspect them first and preserve source provenance in the final artifact.

Guardrails

  • Do not invent consensus estimates, market prices, valuation multiples, or filing data.
  • Do not use a single unsourced chart or article as the basis for a financial conclusion.
  • Do not hide assumptions inside prose; put them in a table or bullet list.
  • Do not mix currencies, fiscal years, adjusted/non-GAAP metrics, or segment definitions without labeling them.
  • Do not externalize or post research without explicit user approval.

Gives 0 of the 12 instructions most research analysis skills give

Counted across 1,063 of the 1,754 authors here whose files we hold, read 2026-08-06

  • generate a markdown reportin 32 of 1063, across 17 files
  • cite each claim's sourcein 31 of 1063, across 14 files
  • define the ideal customer profilein 20 of 1063, across 2 files
  • search for companies matching the criteriain 20 of 1063, across 2 files
  • assign a fit score from one to tenin 20 of 1063, across 2 files
  • format results in a scannable markdown templatein 20 of 1063, across 2 files
  • analyze the codebase to understand the productin 19 of 1063, across 1 file
  • ask clarifying questions about the value propositionin 19 of 1063, across 1 file
  • look for signals of immediate needin 19 of 1063, across 1 file
  • identify the target decision maker rolein 19 of 1063, across 1 file
  • suggest a personalized contact strategyin 19 of 1063, across 1 file
  • provide conversation starters for outreachin 19 of 1063, across 1 file

Said here and by no other author read

  • draft analyst work product for human review
  • confirm ticker, exchange, coverage universe, and geography if missing
  • use web browsing when answer depends on current information
  • label uncertainty and stale data
  • put model assumptions in a table or bullet list
  • read workflow checklists before drafting deliverable

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.