Agent skill

Earnings Preview Single

by w95 in w95/awesome-claude-corporate-skills

Generate a concise 4-5 page equity research earnings preview for a single company.

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Earnings Preview Single

skills CLI
$ npx skills add w95/awesome-claude-corporate-skills --skill earnings-preview-single -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install w95/awesome-claude-corporate-skills earnings-preview-single --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/02-finance-accounting/spglobal-earnings-preview .claude/skills/earnings-preview-single && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
earnings-preview-single
GitHub stars
239
Used in
1 other repo
Token cost
~9.3k tokens
SKILL.md length
4,008 words
Files
3
Skills in repo
42
Repo updated
First seen
Licence
Apache-2.0

At a glance

Generate a concise 4-5 page equity research earnings preview for a single company.

  • Works in 8 steps: Company Profile & Setup → Earnings Transcript Analysis (MANDATORY… → Competitor Analysis → …
  • Tasks that involve Stock and market analysis
  • SKILL.md covers Phase 1: Company Profile & Setup, Phase 2: Earnings Transcript…, Phase 3: Competitor Analysis and Phase 4: News, Estimates &…, plus 5 more sections
  • Reaches investing.com

What it does

Earnings Preview Single is an agent skill from w95/awesome-claude-corporate-skills. Generate a concise 4-5 page equity research earnings preview for a single company. Analyzes the most recent earnings transcript, competitor landscape, valuation, and recent news to produce a professional HTML report.

Its SKILL.md is about 9.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `report-template.md`).

It sits in Business, Finance & HR, covering Stock and market analysis. It works with Model Context Protocol. The repository describes itself as: 166 production-ready Claude AI skills organized by corporate role — executive leadership, finance, HR, marketing, sales, legal, operations, engineering, product, data, customer…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Stock and market analysis

Example prompts

  • “/earnings-preview-single”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Company Profile & Setup
  2. Earnings Transcript Analysis (MANDATORY — COMPLETE BEFORE WRITING)
  3. Competitor Analysis
  4. News, Estimates & Sector Intelligence (via Kensho Grounding)
  5. Financial Data Collection
  6. Verification & Calculations (MANDATORY — DO NOT SKIP)
  7. Generate the HTML Report
  8. Output

What it can do on your machine

Read from SKILL.md and the folder at commit 78dbc7c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are html).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • investing.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Earnings Preview Single loads about 9.3k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 4,008 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~9.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from w95/awesome-claude-corporate-skills at commit 78dbc7c, republished under its Apache-2.0 licence (© w95). 4,008 words, ~9,329 tokens.

Download SKILL.mdSave it as .claude/skills/earnings-preview-single/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
earnings-preview-single
description
Generate a concise 4-5 page equity research earnings preview for a single company. Analyzes the most recent earnings transcript, competitor landscape, valuation, and recent news to produce a professional HTML report.

Single-Company Earnings Preview

Generate a concise, professional equity research earnings preview for a single company. The output is a self-contained HTML file targeting 4-5 printed pages. The report is dense with figures and data, with tight narrative that gets straight to the point.

Data Sources (ZERO EXCEPTIONS): The ONLY permitted data sources are Kensho Grounding MCP (search) and S&P Global MCP (kfinance). Absolutely NO other tools, data sources, or web access of any kind. Specifically:

  • Do NOT use WebSearch, WebFetch, web_search, brave_search, google_search, or ANY generic web/internet search tool — even if Kensho is slow, returns no results, or is temporarily unavailable.
  • Do NOT use any browser, URL fetch, or web scraping tool.
  • If Kensho Grounding returns no results for a query, try rephrasing the query or note "data not available" in the report. NEVER fall back to web search as an alternative.
  • Every piece of information in the report must be traceable to either a kfinance MCP function call or a Kensho search call. If it cannot be sourced to one of these two, it must not appear in the report.

Critical Rule: You MUST complete ALL research and data collection (Phases 1-5) BEFORE writing any part of the report.

Intermediate File Rule: All raw data from MCP tool calls MUST be written to files in /tmp/earnings-preview/ immediately after each tool call returns — before moving to the next call. This protects data from context window compression. Do NOT hold data only in memory. At the start of Phase 1, run mkdir -p /tmp/earnings-preview to create the directory. Before generating the HTML report (Phase 7), you MUST read ALL intermediate files back into context using cat commands. The files — not your memory of earlier conversation — are the single source of truth for every number, quote, and source URL in the report. If you skip reading the files, the report WILL contain errors.

Fiscal Quarter Rule: NEVER infer the fiscal quarter from the calendar report date. Many companies have non-standard fiscal years (e.g., Walmart's FY ends Jan 31, so a Feb 2026 report covers Q4 FY2026, not Q4 2025 or Q1 2026). Always use the fiscal quarter and fiscal year exactly as stated in the earnings call name returned by get_next_earnings_from_identifiers or get_earnings_from_identifiers (e.g., "Walmart Q4 FY2026 Earnings Call" means the quarter is Q4 FY2026). Use that verbatim in the report title, headers, tables, and all references. If the call name is ambiguous, cross-reference with get_financial_line_item_from_identifiers period labels.

Length Rule: The report must be concise. Target 4-5 pages when printed. Do NOT write long multi-paragraph narratives. Use tight, punchy bullet points. Every sentence must earn its place. If you can say it in fewer words, do so.

Verbatim Quote Rule: When quoting management in <blockquote> tags, the text MUST be copied exactly from the transcript — word for word, including filler words and sentence fragments. Do NOT paraphrase, rearrange, combine sentences from different parts of the transcript, or "clean up" quotes. If you cannot find the exact phrase in the transcript, do NOT present it as a direct quote. Instead, paraphrase in your own narrative voice without blockquote formatting (e.g., "Management noted that data center demand remains significant"). Every blockquote must be a verbatim, copy-paste excerpt that can be verified against the transcript.

Calculation Integrity Rule: For any multi-step calculation (implied quarterly figures from annual guidance, LTM P/E, y/y growth rates, segment y/y changes), write out each step explicitly and verify intermediate results before using them in the next step. If you state A + B + C = X, verify X is arithmetically correct before using X in a subsequent formula. If the appendix shows a sum that does not equal its stated components, the report is wrong. When in doubt, recompute from raw data rather than reusing a previously calculated intermediate.

Ratio Nomenclature Rule: All valuation ratios must be explicitly labeled as LTM (Last Twelve Months) or NTM (Next Twelve Months). Never use "trailing" or "forward" — always use LTM or NTM. LTM ratios use the sum of the most recent 4 reported quarters. NTM ratios use the sum of the next 4 quarterly consensus mean EPS estimates from get_consensus_estimates_from_identifiers — NOT a single annual figure. Both LTM and NTM P/E must be computed and displayed in the competitor comparison table.

Hyperlink Rule (STRICTLY ENFORCED): Every claim in the report — numeric AND non-numeric — MUST be wrapped in an <a href="#ref-N" class="data-ref"> hyperlink pointing to the corresponding entry in the Appendix. This is not optional. Every single number in the report must be a clickable link. This includes: revenue figures, EPS, margins, growth rates, market caps, P/E ratios, stock returns, price targets, segment revenue, and any other financial metric. It also includes qualitative claims from transcripts or Kensho searches. If you state it as fact, it must link to a source. Assign each unique claim a sequential reference ID (ref-1, ref-2, etc.). The hyperlink style is subtle — navy color, no underline, dotted underline on hover. Do NOT write any number in the report body without wrapping it in an <a> tag. Example: write <a href="#ref-1" class="data-ref">$152.3B</a>, NEVER write $152.3B as plain text.


Phase 1: Company Profile & Setup

  1. Parse the single company ticker from $ARGUMENTS (strip whitespace).
  2. Run mkdir -p /tmp/earnings-preview to create the working directory.
  3. Call get_latest() to establish current reporting period context.
  4. Call get_info_from_identifiers — record market cap, industry.
  5. Call get_company_summary_from_identifiers — record business description.
  6. Call get_next_earnings_from_identifiers — record upcoming earnings date and fiscal quarter name.

Immediately write /tmp/earnings-preview/company-info.txt:

TICKER: [ticker]
COMPANY: [full name]
INDUSTRY: [industry]
MARKET_CAP: [value] (as of [date])
NEXT_EARNINGS_DATE: [date]
NEXT_EARNINGS_QUARTER: [Q# FY#### exactly as returned by API]
BUSINESS_DESCRIPTION: [2-3 sentence summary]

Phase 2: Earnings Transcript Analysis (MANDATORY — COMPLETE BEFORE WRITING)

  1. Call get_latest_earnings_from_identifiers to get the most recent completed earnings call key_dev_id.
  2. Call get_transcript_from_key_dev_id for that transcript.
  3. Immediately write /tmp/earnings-preview/transcript-extracts.txt with the following sections. Write this file WHILE you still have the transcript in context — do not wait:
TRANSCRIPT_SOURCE: [Call Name, e.g., "Q3 2025 Earnings Call"]
KEY_DEV_ID: [key_dev_id]
CALL_DATE: [date]
FISCAL_QUARTER: [Q# FY####]

=== VERBATIM QUOTES (copy-paste exactly — do NOT paraphrase) ===
QUOTE_1: "[exact text from transcript]"
SPEAKER_1: [Name], [Title]
CONTEXT_1: [1 sentence on where this appeared — prepared remarks or Q&A]

QUOTE_2: "[exact text from transcript]"
SPEAKER_2: [Name], [Title]
CONTEXT_2: [context]

QUOTE_3: "[exact text from transcript]"
SPEAKER_3: [Name], [Title]
CONTEXT_3: [context]

QUOTE_4: "[exact text from transcript]"
SPEAKER_4: [Name], [Title]
CONTEXT_4: [context]

=== GUIDANCE (quantitative only) ===
- [metric]: [range or point estimate as stated by management]
- [metric]: [range or point estimate]

=== KEY DRIVERS ===
- [driver 1 with supporting data point]
- [driver 2 with supporting data point]
- [driver 3 with supporting data point]

=== HEADWINDS & RISKS ===
- [risk 1 with quantification if available]
- [risk 2]

=== ANALYST Q&A THEMES ===
- [theme 1: what analysts pushed on]
- [theme 2]
- [theme 3]

=== SYNTHESIS: THEMES TO WATCH NEXT QUARTER ===
- [theme 1]
- [theme 2]
- [theme 3]

Phase 3: Competitor Analysis

  1. Call get_competitors_from_identifiers with competitor_source="all".
  2. Select top 5-7 most relevant public competitors.
  3. For the company AND all selected competitors, gather:
    • get_prices_from_identifiers with periodicity="day", last 12 months
    • get_financial_line_item_from_identifiers for diluted_eps, period_type="quarterly", num_periods=8
    • get_capitalization_from_identifiers with capitalization="market_cap" (latest)
    • get_consensus_estimates_from_identifiers with period_type="quarterly", num_periods_forward=4 — this returns consensus mean EPS estimates for the next 4 quarters, which are summed to compute NTM EPS

After each tool call returns, immediately append the raw data to the appropriate intermediate file:

Write /tmp/earnings-preview/prices.csv — one row per (ticker, date, close). Include the source column with the exact MCP function call. Write the subject company's prices first, then each competitor's as you fetch them:

ticker,date,close,source
D,2025-02-19,55.67,get_prices_from_identifiers(identifier='D',periodicity='day')
D,2025-02-20,55.82,get_prices_from_identifiers(identifier='D',periodicity='day')
...
DUK,2025-02-19,111.79,get_prices_from_identifiers(identifier='DUK',periodicity='day')
...

Note: the source value is the same for all rows from a single call — write it on every row so it's always available.

Write /tmp/earnings-preview/peer-eps.csv — one row per (ticker, period, eps). Write immediately after each diluted_eps call:

ticker,period,diluted_eps,source
D,Q4 2024,1.09,get_financial_line_item_from_identifiers(identifier='D',line_item='diluted_eps',period_type='quarterly')
D,Q1 2025,-0.11,get_financial_line_item_from_identifiers(identifier='D',line_item='diluted_eps',period_type='quarterly')
...
DUK,Q4 2024,1.52,get_financial_line_item_from_identifiers(identifier='DUK',line_item='diluted_eps',period_type='quarterly')
...

Write /tmp/earnings-preview/peer-market-caps.csv — one row per ticker. Write immediately after each market_cap call:

ticker,market_cap,retrieval_date,source
D,55900000000,2026-02-19,get_capitalization_from_identifiers(identifier='D',capitalization='market_cap')
DUK,98300000000,2026-02-19,get_capitalization_from_identifiers(identifier='DUK',capitalization='market_cap')
...

Write /tmp/earnings-preview/consensus-eps.csv — one row per (ticker, period, consensus mean EPS). Write immediately after each get_consensus_estimates_from_identifiers call:

ticker,period,consensus_mean_eps,num_estimates,source
D,Q4 2025,0.88,12,get_consensus_estimates_from_identifiers(identifier='D',period_type='quarterly',num_periods_forward=4)
D,Q1 2026,0.72,10,get_consensus_estimates_from_identifiers(identifier='D',period_type='quarterly',num_periods_forward=4)
D,Q2 2026,0.91,9,get_consensus_estimates_from_identifiers(identifier='D',period_type='quarterly',num_periods_forward=4)
D,Q3 2026,1.05,8,get_consensus_estimates_from_identifiers(identifier='D',period_type='quarterly',num_periods_forward=4)
DUK,Q4 2025,1.48,14,get_consensus_estimates_from_identifiers(identifier='DUK',period_type='quarterly',num_periods_forward=4)
...
  1. Do NOT calculate P/E or returns yet. The raw data is now on disk. Calculations happen in Phase 6 (Verification), reading from these files.

Date Consistency Rule (stock returns): When computing comparative stock returns (YTD %, 1-yr %, 30d %, 90d %), ALL tickers MUST use the exact same start and end dates. After writing all price data to prices.csv, identify the first trading date that appears in ALL tickers' data and use that as the common base date. Do NOT use different base dates for different tickers (e.g., the subject from Feb 19 and peers from Feb 28). If a ticker's data starts later than others, use the first overlapping date for ALL calculations. State the common base date in the appendix for every return calculation.

P/E Currency Rule (LTM P/E): When computing LTM P/E for each company, use that company's most recent 4 reported quarters from peer-eps.csv — not a fixed calendar window applied to all. If a peer has already reported Q4 2025 while the subject company has only reported through Q3 2025, the peer's LTM EPS should include Q4 2025. Check the latest reported period for each company and use the 4 most recent periods per company. Note in the appendix which 4 quarters were used for each P/E calculation.

Market Cap Date-Stamp: When reporting market cap, use the retrieval_date from peer-market-caps.csv. If it differs from the report date, note this in the appendix.


Phase 4: News, Estimates & Sector Intelligence (via Kensho Grounding)

Run these search queries for each category below. Do NOT skip any.

CRITICAL — Capture Source URLs: Every Kensho search result includes a source URL for the underlying article, report, or data page. You MUST record the URL alongside each finding.

After EACH search call, immediately append the results to /tmp/earnings-preview/kensho-findings.txt using the format below. Do NOT wait until all searches are done — write after each one:

=== SEARCH: "[query used]" ===
DATE_RUN: [today's date]
CATEGORY: [estimates|analyst_ratings|risks|news|sector]

FINDING_1: [key finding or excerpt]
URL_1: [source URL from search result]
SOURCE_1: [publication name, date if available]

FINDING_2: [key finding or excerpt]
URL_2: [source URL]
SOURCE_2: [publication name, date]

[...continue for all relevant results from this search...]

Earnings estimates & analyst sentiment:

  1. search for "[TICKER] earnings estimates consensus EPS revenue upcoming quarter"
    • Record: consensus EPS, consensus revenue, estimate revision direction over last 90 days.
    • Append to kensho-findings.txt immediately.
  2. search for "[TICKER] analyst ratings price target upgrades downgrades"
    • Record: recent upgrades/downgrades, price target range, bull/bear thesis summaries.
    • Append to kensho-findings.txt immediately.
  3. search for "[TICKER] risks bear case concerns investors"
    • Record: key debates, bear arguments, swing factors for the upcoming print.
    • Append to kensho-findings.txt immediately.

Recent news (MANDATORY — do not skip): 4. search for "[TICKER] [company name] recent news developments"

  • Record: material news from the last 60 days — M&A, product launches, executive changes, regulatory actions, partnerships, legal developments, tariffs, or any event that could affect the upcoming earnings print or forward guidance.
  • For each item, note the date, headline, potential earnings impact.
  • Append to kensho-findings.txt immediately.

Sector context: 5. search for "[company industry/sector] sector outlook trends"

  • Record: sector-level tailwinds/headwinds, macro data, competitive dynamics.
  • Append to kensho-findings.txt immediately.

Phase 5: Financial Data Collection

Quarterly financials (last 8 quarters): get_financial_line_item_from_identifiers with period_type="quarterly", num_periods=8 for: revenue, gross_profit, operating_income, ebitda, net_income, diluted_eps

After each line item call returns, immediately append to /tmp/earnings-preview/financials.csv. Write the raw values exactly as returned — do NOT round or convert yet. Include the source column with the exact MCP function call and parameters:

ticker,period,line_item,value,source
D,Q4 2024,revenue,3941000000,get_financial_line_item_from_identifiers(identifier='D',line_item='revenue',period_type='quarterly')
D,Q1 2025,revenue,3400000000,get_financial_line_item_from_identifiers(identifier='D',line_item='revenue',period_type='quarterly')
D,Q2 2025,revenue,4076000000,get_financial_line_item_from_identifiers(identifier='D',line_item='revenue',period_type='quarterly')
D,Q3 2025,revenue,3810000000,get_financial_line_item_from_identifiers(identifier='D',line_item='revenue',period_type='quarterly')
D,Q4 2024,diluted_eps,1.09,get_financial_line_item_from_identifiers(identifier='D',line_item='diluted_eps',period_type='quarterly')
D,Q1 2025,diluted_eps,-0.11,get_financial_line_item_from_identifiers(identifier='D',line_item='diluted_eps',period_type='quarterly')
...

Do NOT calculate margins or growth rates yet. Write raw data only. Calculations happen in Phase 6.

Segment data:

  • get_segments_from_identifiers with segment_type="business", period_type="quarterly", num_periods=8
  • You need 8 quarters (not 4) so you have the year-ago quarter for y/y comparisons. To calculate y/y for Q3 2025, you need Q3 2024 — which is the 5th quarter back. If the prior-year quarter's segment data is not available in the API response, do NOT estimate or fabricate it. State "y/y not available" in the report.

Immediately write /tmp/earnings-preview/segments.csv:

ticker,period,segment_name,revenue,source
D,Q3 2024,Dominion Energy Virginia,2762000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
D,Q3 2024,Dominion Energy South Carolina,848000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
D,Q3 2024,Contracted Energy,260000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
D,Q3 2025,Dominion Energy Virginia,3311000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
D,Q3 2025,Dominion Energy South Carolina,945000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
D,Q3 2025,Contracted Energy,297000000,get_segments_from_identifiers(identifier='D',segment_type='business',period_type='quarterly')
...

Earnings history (for stock chart annotations):

  • get_earnings_from_identifiers — collect past earnings dates within the 12-month price window.
  • Immediately write /tmp/earnings-preview/earnings-dates.csv:
ticker,earnings_date,call_name,source
D,2025-05-02,Q1 2025 Earnings Call,get_earnings_from_identifiers(identifier='D')
D,2025-08-01,Q2 2025 Earnings Call,get_earnings_from_identifiers(identifier='D')
D,2025-10-31,Q3 2025 Earnings Call,get_earnings_from_identifiers(identifier='D')
...

Phase 6: Verification & Calculations (MANDATORY — DO NOT SKIP)

Before generating the report, read back ALL intermediate files and perform calculations from the clean data. This phase ensures data integrity by working from files rather than compressed conversation context.

  1. Read all intermediate files using bash cat commands:

    • cat /tmp/earnings-preview/company-info.txt
    • cat /tmp/earnings-preview/transcript-extracts.txt
    • cat /tmp/earnings-preview/financials.csv
    • cat /tmp/earnings-preview/segments.csv
    • cat /tmp/earnings-preview/prices.csv
    • cat /tmp/earnings-preview/peer-eps.csv
    • cat /tmp/earnings-preview/peer-market-caps.csv
    • cat /tmp/earnings-preview/consensus-eps.csv
    • cat /tmp/earnings-preview/kensho-findings.txt
    • cat /tmp/earnings-preview/earnings-dates.csv
  2. Calculate derived metrics from the raw data now in context:

    • Gross margin % = gross_profit / revenue (per quarter)
    • Operating margin % = operating_income / revenue (per quarter)
    • Revenue y/y growth % = (current Q revenue - year-ago Q revenue) / year-ago Q revenue
    • EPS y/y growth % = same logic; use "n.m." if base is negative
    • Segment y/y growth % = match segment by name to year-ago Q; if missing, note "y/y not available"
    • LTM P/E per company = latest price / sum of most recent 4 quarterly EPS (check which 4 quarters are available per ticker using peer-eps.csv)
    • NTM P/E per company = latest price / NTM EPS, where NTM EPS = sum of the next 4 quarterly consensus mean EPS estimates from consensus-eps.csv. Add all 4 quarters' consensus_mean_eps values for each ticker. If fewer than 4 forward quarters are available for a peer, mark NTM P/E as "n/a". Note in the appendix which 4 quarters were summed.
    • Stock returns (YTD, 1-yr, 30d, 90d) = find the common first date across all tickers in prices.csv, then compute returns from that date
  3. Cross-check:

    • Verify every segment y/y has the actual prior-year row in segments.csv. If not, mark "y/y not available."
    • Verify all stock return base dates are identical across tickers.
    • Verify any multi-step calculation by re-summing components (e.g., LTM EPS sum matches the 4 quarterly values).
    • Verify all verbatim quotes in transcript-extracts.txt are exact copy-pastes (not paraphrases).
  4. Write /tmp/earnings-preview/calculations.csv with all derived values:

ticker,metric,value,formula,components
D,gross_margin_Q3_2025,32.5%,gross_profit/revenue,"gross_profit=1238100000,revenue=3810000000"
D,revenue_yoy_Q3_2025,+9.3%,(Q3_2025-Q3_2024)/Q3_2024,"Q3_2025=3810000000,Q3_2024=3486000000"
D,ltm_pe,24.2x,price/ltm_eps,"price=65.46,ltm_eps=2.70,quarters=Q4_2024+Q1_2025+Q2_2025+Q3_2025"
D,ntm_pe,18.5x,price/ntm_eps,"price=65.46,ntm_eps=3.56,quarters=Q4_2025(0.88)+Q1_2026(0.72)+Q2_2026(0.91)+Q3_2026(1.05),source=get_consensus_estimates_from_identifiers"
D,yoy_return,+17.6%,(end-start)/start,"end=65.46,start=55.67,base_date=2025-02-19"
DUK,yoy_return,+13.0%,(end-start)/start,"end=126.32,start=111.79,base_date=2025-02-19"
...

This file becomes the single source of truth for all numbers in the report.


Phase 7: Generate the HTML Report

STOP — BEFORE WRITING ANY HTML, YOU MUST READ ALL INTERMEDIATE FILES. THIS IS A BLOCKING PREREQUISITE.

This is not optional. You MUST run each cat command below as a separate bash tool call (not combined into one). This ensures each file's contents are individually loaded and visible in the conversation. Do NOT combine them into a single command. Do NOT skip any file.

Run these commands one at a time, each as its own bash call:

  1. cat /tmp/earnings-preview/company-info.txt
  2. cat /tmp/earnings-preview/transcript-extracts.txt
  3. cat /tmp/earnings-preview/financials.csv
  4. cat /tmp/earnings-preview/segments.csv
  5. cat /tmp/earnings-preview/prices.csv
  6. cat /tmp/earnings-preview/peer-eps.csv
  7. cat /tmp/earnings-preview/peer-market-caps.csv
  8. cat /tmp/earnings-preview/consensus-eps.csv
  9. cat /tmp/earnings-preview/kensho-findings.txt
  10. cat /tmp/earnings-preview/earnings-dates.csv
  11. cat /tmp/earnings-preview/calculations.csv

After reading ALL files, you MUST print a summary message to the user that lists every file and its status. Use exactly this format:

--- DATA FILE VERIFICATION ---
1. company-info.txt        ✓ loaded ([N] lines)
2. transcript-extracts.txt ✓ loaded ([N] lines)
3. financials.csv          ✓ loaded ([N] rows)
4. segments.csv            ✓ loaded ([N] rows)
5. prices.csv              ✓ loaded ([N] rows)
6. peer-eps.csv            ✓ loaded ([N] rows)
7. peer-market-caps.csv    ✓ loaded ([N] rows)
8. consensus-eps.csv       ✓ loaded ([N] rows)
9. kensho-findings.txt     ✓ loaded ([N] lines)
10. earnings-dates.csv     ✓ loaded ([N] rows)
11. calculations.csv       ✓ loaded ([N] rows)

All intermediate data files loaded successfully.
Generating report using file data as the single source of truth.
---

If any file is missing or empty, STOP and tell the user which file failed. Do NOT proceed to generate the report with missing data.

Every number, quote, source URL, and MCP function call reference in the HTML report must come from these files — not from your memory of earlier conversation turns. The files are the single source of truth. Earlier conversation context may have been compressed or summarized and WILL contain errors if relied upon. If a data point is not in the files, it should not appear in the report.

See report-template.md for the complete HTML template, CSS, and Chart.js configuration.

MANDATORY — Use Template Helper Functions for Charts: The report-template.md provides pre-built, debugged Chart.js helper functions. You MUST use these exact functions to create charts. Do NOT write custom inline Chart.js code. The helpers are:

  • createRevEpsChart(canvasId, labels, revenueData, epsData, revLabel) — for Figure 1
  • createMarginChart(canvasId, labels, grossMargins, opMargins) — for Figure 2
  • createRevGrowthChart(canvasId, labels, growthData) — for Figure 3
  • createAnnotatedPriceChart(canvasId, labels, prices, earningsDates, ticker) — for Figure 5
  • createCompPerfChart(canvasId, labels, datasets) — for Figure 6
  • createPEChart(canvasId, companies) — for Figure 7

Each chart call MUST be in its own <script> tag wrapped in a try-catch block. This ensures a bug in one chart does not prevent other charts from rendering. Example:

html
<script>
try {
  createRevEpsChart('chart-rev-eps', [...], [...], [...], 'Revenue ($B)');
} catch(e) { console.error('Figure 1 error:', e); }
</script>
<script>
try {
  createMarginChart('chart-margins', [...], [...], [...]);
} catch(e) { console.error('Figure 2 error:', e); }
</script>
Show full SKILL.md (1,597 more words)Show less
Report Structure (4-5 pages total)

The report has two halves: narrative (pages 1-2) and figures (pages 3-5). Keep these tightly integrated.


AI DISCLAIMER (MANDATORY — must appear in 3 places): You MUST include the following disclaimer text in the report HTML. This is not optional — the report is incomplete without it:

"Analysis is AI-generated — please confirm all outputs"

It must appear in exactly these 3 locations:

  1. Header banner — immediately before the cover header, as a centered yellow banner: <div class="ai-disclaimer">Analysis is AI-generated — please confirm all outputs</div>
  2. Footer — inside the page-footer div, as a prominent yellow banner: <div class="footer-disclaimer">Analysis is AI-generated — please confirm all outputs</div>
  3. Appendix — as the first line of the appendix section, before the table: <div class="ai-disclaimer">Analysis is AI-generated — please confirm all outputs</div>

PAGE 1: Cover & Thesis

  • AI disclaimer banner (yellow, centered — see AI DISCLAIMER rule above)
  • Header: Company name (TICKER) | Industry | Report date
  • Title: Thematic, specific to the quarter (e.g., "Walmart Inc. (WMT) Q4 FY2026 Earnings Preview: Holiday Harvest — Can Furner's First Print Confirm the $1T Thesis?")
  • Executive thesis (2-3 short paragraphs max with bullet points):
    • What we expect from this print in 1-2 sentences
    • 4-6 bullet points covering: our EPS estimate vs consensus, guidance expectations, key metrics to watch, what would move the stock, key debates
    • Keep it direct and opinionated — take a view, don't hedge everything
  • Key management quotes from the most recent earnings call woven into the narrative where relevant. Do NOT put these under a separate heading. Integrate them naturally as supporting evidence for your thesis points. Format as indented blockquotes.

PAGE 2: Estimates, Themes & News

  • Consensus Estimates Table (single table, labeled as a figure):

    • Columns: Metric | Consensus | Our Estimate | y/y Change
    • Rows: Revenue, EPS, Gross Margin, Operating Income, and 2-3 company-specific KPIs that matter (e.g., comp sales, eComm growth, membership revenue — whatever the Street cares about for THIS company)
    • Color-coding is strictly mechanical: If the y/y change value is negative, use class="neg" (red). If positive, use class="pos" (green). If zero or N/A, use class="neutral". The sign of the number determines the class — do NOT override based on interpretation. A -1.1% is ALWAYS red, even if the decline is small.
    • This is the ONLY guidance/estimates section. Do not repeat estimate data elsewhere.
  • Key Metrics Beyond Headline EPS (bulleted list, 3-5 items):

    • The specific metrics that will determine if this is a good or bad quarter beyond the EPS number
    • For each: what the metric is, what consensus/management expects, why it matters
    • Be specific: "Walmart Connect ad revenue growth (consensus ~30% y/y, 3Q was 33%)"
  • Themes to Watch (3-5 bullets):

    • Forward-looking items for the upcoming report
    • What management needs to deliver on, what could surprise, what the bears are focused on
    • Each theme: 1-2 sentences max
  • Recent News & Developments (3-5 bullets):

    • Material news from the last 60 days, one line each
    • Date + headline + brief impact assessment
    • Only include items that could affect the upcoming print or guidance

PAGES 3-5: Figures (all charts and tables)

All figures are numbered sequentially. Every figure has a title and source line.

  • Figure 1: Quarterly Revenue & Diluted EPS — Bar/line combo, 8 quarters
  • Figure 2: Margin Trends (Gross & Operating %) — Dual line chart, 8 quarters
  • Figure 3: Revenue Growth y/y % — Bar chart with green/red conditional coloring. Only include quarters where both current and year-ago data exist (typically the most recent 4 quarters from the 8 fetched). Do NOT include quarters where y/y cannot be computed — the chart should have 4 bars, not 8.
  • Figure 4: Business Segment Revenue — Table: Segment | Latest Q Rev ($M) | % of Total | y/y Change
  • Figure 5: 1-Year Stock Price with Earnings Dates — Price line with vertical annotation lines at earnings dates, labeled with quarter and 1-day post-earnings move
  • Figure 6: Stock Performance vs. Competitors (Indexed to 100) — Multi-line chart, subject company as thick solid line, competitors as thinner dashed lines
  • Figure 7: LTM P/E vs. Competitors — Horizontal bar chart, subject company highlighted in navy
  • Figure 8: Competitor Comparison Table — Ticker | Company | Mkt Cap | LTM P/E | NTM P/E | YTD % | 1-Yr %

APPENDIX: Data Sources & Calculations (MANDATORY — DO NOT SKIP OR ABBREVIATE)

The appendix MUST begin with the AI disclaimer banner: <div class="ai-disclaimer">Analysis is AI-generated — please confirm all outputs</div>

The final page(s) of the report MUST include an Appendix table that documents every claim — numeric and non-numeric — cited in the report. Every number that appears in the report body must have a corresponding row in this appendix, and every such number in the report body must be a clickable <a href="#ref-N"> hyperlink that scrolls to its appendix row. If a number appears in the report without a hyperlink to the appendix, the report is incomplete.

  • Table columns: Ref # | Fact | Value | Source & Derivation

  • Ref #: Sequential ID matching the hyperlink anchors in the report body (ref-1, ref-2, etc.). Each row has an id="ref-N" attribute so hyperlinks scroll to it.

  • Fact: Human-readable label (e.g., "Q3 FY2026 Revenue", "LTM P/E — WMT", "Management flagged tariff headwinds", "Barclays upgraded to Overweight")

  • Value: The exact figure as displayed in the report (e.g., "$152.3B", "24.5%", "28.1x"). For non-numeric facts, leave blank or write "N/A".

  • Source & Derivation: This is the critical column. Every row must have a specific, detailed source — not just a label. Follow these rules strictly:

    For raw financial data from S&P Capital IQ (revenue, EPS, gross profit, operating income, net income, EBITDA, prices, market cap, etc.):

    • State the MCP function used and its key parameters. Format: S&P Capital IQ — [function_name](identifier='[TICKER]', line_item='[item]', period_type='[type]', period='[Q# FY####]')
    • Examples:
      • S&P Capital IQ — get_financial_line_item_from_identifiers(identifier='WMT', line_item='revenue', period_type='quarterly', period='Q3 FY2026')
      • S&P Capital IQ — get_financial_line_item_from_identifiers(identifier='WMT', line_item='diluted_eps', period_type='quarterly', period='Q3 FY2026')
      • S&P Capital IQ — get_prices_from_identifiers(identifier='WMT', periodicity='day')
      • S&P Capital IQ — get_capitalization_from_identifiers(identifier='WMT', capitalization='market_cap')
    • Do NOT just write "S&P Capital IQ" with no detail. The reader must know exactly which data point from which tool call produced this number.

    For calculated values (margins, growth rates, P/E, returns, y/y changes):

    • Show the full formula with hyperlinked components — each component must be an <a href="#ref-N"> link back to the appendix row for that raw data point. This is critical: the reader must be able to click through from the calculated value to each of its inputs.
    • Example: Gross Margin = <a href='#ref-5'>Gross Profit $37.2B</a> / <a href='#ref-1'>Revenue $152.3B</a> = 24.4%. Source: S&P Capital IQ (calculated)
    • Example: LTM P/E = <a href='#ref-20'>Price $172.35</a> / (<a href='#ref-8'>Q1 EPS $1.47</a> + <a href='#ref-9'>Q2 EPS $1.84</a> + <a href='#ref-10'>Q3 EPS $1.53</a> + <a href='#ref-11'>Q4 EPS $1.80</a>) = $172.35 / $6.64 = 25.9x
    • Example: Revenue y/y growth = (<a href='#ref-12'>Q3 FY26 Rev $165.8B</a> - <a href='#ref-3'>Q3 FY25 Rev $160.8B</a>) / <a href='#ref-3'>Q3 FY25 Rev $160.8B</a> = +3.1%
    • Every formula component must be a clickable hyperlink. Do NOT write formulas with plain-text numbers.

    For transcript-sourced claims (quotes, management commentary, guidance):

    • Write the verbatim excerpt sentence from the transcript.
    • Reference the transcript by its full name and the key_dev_id used to fetch it.
    • Format: "[verbatim quote]" — [Speaker], [Title]. Source: [Q# FY#### Earnings Call Transcript] (key_dev_id: [ID])
    • Example: "We expect comp sales growth of 3-4% in Q4" — CEO John Furner. Source: Q3 FY2026 Earnings Call Transcript (key_dev_id: 12345678)

    For Kensho Grounding search results (news, analyst ratings, consensus estimates):

    • Write the key finding or excerpt from the search result.
    • MANDATORY: Include the source URL returned by the Kensho search tool as a clickable <a href="[URL]" target="_blank"> hyperlink. This is the most important part — readers must be able to click through to the original source.
    • Format: "[finding/excerpt]" — <a href="[URL]" target="_blank">[Source Title or Publication]</a>. Query: search("[query used]")
    • Example: "Barclays upgraded WMT to Overweight with $210 price target on Jan 15, 2026." — <a href="https://www.investing.com/news/barclays-upgrades-wmt" target="_blank">Investing.com, Jan 15 2026</a>. Query: search("WMT analyst ratings price target upgrades downgrades")
    • If no URL was returned for a particular result, write "Source URL not available" and still include the search query.

Completeness check: Before finalizing the report, scan every number in the report body. If any number is not wrapped in <a href="#ref-N" class="data-ref">, fix it. If any appendix row has a Source & Derivation that is just a bare label like "S&P Capital IQ" with no function call detail, fix it. If any calculated value's formula lacks hyperlinked components, fix it. If any Kensho-sourced claim lacks a source URL, fix it.

Group the appendix rows by section (Financials, Valuation, Estimates & Consensus, Transcript Claims, News & Analyst Commentary, Stock Performance) with subheadings. Use smaller font size (10-11px).


Phase 8: Output

  1. Write the complete HTML file to earnings-preview-[TICKER]-YYYY-MM-DD.html in the current working directory.
  2. Open it in the browser: open earnings-preview-[TICKER]-YYYY-MM-DD.html
  3. Tell the user the file has been created and summarize the key findings.

Writing Guidelines

  • NO EMOJIS: Do not use any emojis anywhere in the report. This is a professional research document.
  • CONCISE: Target 4-5 printed pages. Every sentence must carry weight. Use bullets, not paragraphs, wherever possible. If a section feels long, cut it.
  • Be specific with numbers: "$52.4B revenue, up 5.2% y/y" not "strong revenue growth."
  • Take a view: This is an earnings preview, not a summary. State what you expect, what matters, and why. Be opinionated but back it with data.
  • Management quotes without headers: Weave 3-4 key management quotes from the most recent call directly into the narrative as blockquotes. Do not create a "Key Management Quotes" section heading — let them flow naturally as supporting evidence.
  • Professional tone: Sell-side equity research style — analytical, direct, data-driven.
  • Charts must use real data: Every chart populated with actual MCP data. Never fabricate.
  • Competitor context: Frame valuation relative to peers. A 25x P/E means nothing without knowing peers trade at 20x or 35x.
  • Hyperlinked claims: Every factual claim — numeric or qualitative — must be an <a class="data-ref"> tag linking to its appendix entry. Numbers: <a href="#ref-1" class="data-ref">$152.3B</a>. Qualitative: <a href="#ref-25" class="data-ref">management flagged tariff headwinds as the primary margin risk</a>. No fact should appear without a traceable source in the appendix.

© w95, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in 02-finance-accounting/spglobal-earnings-preview of w95/awesome-claude-corporate-skills.

  • SKILL.md
  • LICENSE
  • report-template.md

Open the folder on GitHubat commit 78dbc7c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in w95/awesome-claude-corporate-skills, which our catalogue first saw on October 7, 2026.

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Questions about Earnings Preview Single

What does Earnings Preview Single do?

Generate a concise 4-5 page equity research earnings preview for a single company. Earnings Preview Single is an agent skill from w95/awesome-claude-corporate-skills. Generate a concise 4-5 page equity research earnings preview for a single company.

When should I use Earnings Preview Single?

Earnings Preview Single fits situations like: tasks that involve Stock and market analysis.

How do I install Earnings Preview Single in Claude Code?

Run `npx skills add w95/awesome-claude-corporate-skills --skill earnings-preview-single -a claude-code`. Or copy the skill folder (02-finance-accounting/spglobal-earnings-preview in w95/awesome-claude-corporate-skills) into .claude/skills/earnings-preview-single in your project. Claude Code loads it when a task matches its description.

How do I install Earnings Preview Single in Codex?

Run `npx skills add w95/awesome-claude-corporate-skills --skill earnings-preview-single -a codex`. Or copy the skill folder (02-finance-accounting/spglobal-earnings-preview in w95/awesome-claude-corporate-skills) into .agents/skills/earnings-preview-single in your project. Codex loads it when a task matches its description.

Can I use Earnings Preview Single in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add w95/awesome-claude-corporate-skills --skill earnings-preview-single -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/earnings-preview-single, .gemini/skills/earnings-preview-single, .github/skills/earnings-preview-single and .opencode/skills/earnings-preview-single in your project.

What does Earnings Preview Single need to run?

SKILL.md names no scripts, command-line tools or credentials: Earnings Preview Single is instructions for the agent only.

Does Earnings Preview Single access the network?

SKILL.md names 1 domain. In commands or code: investing.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Earnings Preview Single safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Earnings Preview Single use?

Earnings Preview Single is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Earnings Preview Single use?

About 9.3k tokens (SKILL.md is roughly 37k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Earnings Preview Single?

Skills that share tags, products or a category with Earnings Preview Single: Stock API (zhangxiangliang/stock-api, 2k stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Agentic Trading Desk (Oft3r/agentic-trading-desk, 306 stars) and Earnings Analysis (Wind-Alice/AliceMarket, 130 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Earnings Preview Single?

w95 (a GitHub user) maintains it in w95/awesome-claude-corporate-skills, which has 239 GitHub stars. The repository holds 42 skills in this directory. The repository was last updated on February 26, 2026.

Source: w95/awesome-claude-corporate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.