# Citation verification audit: MRVL

## sec-filing-and-facts
Passed: True
Return code: 0

### stdout
```
Query: You are a fresh context window citation verifier subagent for the MRVL 
equity report.

Files to inspect:
- HTML report: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports
/mrvl-deep-dive-2026-06-03.html
- Structured generation data: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/process
ed/generated_reports_20260603_mrvl.json

Use your tools directly. Do not assume citations are correct just because they 
appear in the report.
Open/read the report and data file. Fetch or inspect cited URLs where possible. 
If a URL is blocked,
record the exact blocker and verify everything still possible from the local 
structured data and URL shape.

Required output format:
VERDICT: PASS or VERDICT: FAIL
Findings:
- concise bullets with exact section/source references
Corrections needed:
- bullets, or "None"

Pass only if the report's citations accurately support the cited claims, source 
labels/dates are honest,
links are valid or accurately described, and calculations are properly tied to 
cited public data.

Role focus: SEC filings and SEC companyfacts.
- Check every citation to SEC 10-Q, 10-K, and companyfacts.
- Verify filing form/date labels match the structured data and linked SEC URLs.
- Check every citation-backed SEC financial metric in the report against the 
structured data: revenue, margins, TTM values, cash, debt, shares, market cap 
components, and valuation inputs.
- Confirm derived calculations are explained as calculations from cited SEC 
facts, not as directly filed facts when they are derived.

Your task is to check every citation within your role scope.
Initializing agent...
────────────────────────────────────────

  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json  0.1s
  ┊ 🔎 grep      SEC|10-Q|10-K|companyfacts|Company Facts|sec.gov|Revenue|cash|debt|shares|market cap|valuation|margin|TTM  0.1s
  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json  0.1s
  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html  0.1s
  ┊ 💻 $         python3 - <<'PY'
import json, re, urllib.request, ssl, sys, textwrap, os
from html.parser import HTMLParser
json_path='/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json'
html_path='/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html'
with open(json_path) as f: data=json.load(f)[0]
with open(html_path) as f: html=f.read()
print('JSON ticker/company/cik/sic:', data['ticker'], data['company'], data['cik'], data['sic'])
print('Filings:')
for k,v in data['filings'].items():
    if k in ('10-Q','10-K'):
        print(k, v)
print('SEC links in HTML:')
for href,text in re.findall(r'<a href="(https://(?:www|data)\.sec\.gov[^"]+)">([^<]+)</a>', html):
    print(text, '=>', href)
print('\nStructured metric facts:')
for key in ['revenue','gross_profit','operating_income','net_income']:
    m=data['metrics'][key]
    print(key, 'annual', m['annual']['val'], m['annual']['form'], m['annual']['filed'], m['annual'].get('start'), m['annual'].get('end'))
    print(key, 'quarter', m['quarter']['val'], m['quarter']['form'], m['quarter']['filed'], m['quarter'].get('start'), m['quarter'].get('end'))
    print(key, 'q_prior', m['quarter_prior']['val'], m['quarter_prior']['form'], m['quarter_prior']['filed'], m['quarter_prior'].get('start'), m['quarter_prior'].get('end'))
    print(key, 'ttm', m['ttm'])
for key in ['cash','debt_current','debt_noncurrent']:
    print(key, data['metrics'][key])
print('shares', data['shares'])
print('price', data['price'])
print('valuation', data['valuation'])
PY  0.1s
  ┊ 💻 $         python3 - <<'PY'
import urllib.request, ssl, json, time
urls=[
('10-Q','https://www.sec.gov/Archives/edgar/data/1835632/000183563226000019/mrvl-20260502.htm'),
('10-K','https://www.sec.gov/Archives/edgar/data/1835632/000183563226000011/mrvl-20260131.htm'),
('companyfacts','https://data.sec.gov/api/xbrl/companyfacts/CIK0001835632.json'),
('submissions','https://data.sec.gov/submissions/CIK0001835632.json')]
headers={'User-Agent':'equityanalysis citation verifier contact@example.com','Accept-Encoding':'identity','Accept':'application/json,text/html,*/*'}
for name,url in urls:
    print('\nFETCH',name,url)
    try:
        req=urllib.request.Request(url, headers=headers)
        with urllib.request.urlopen(req, timeout=30) as r:
            data=r.read(5000)
            print('status', r.status, 'content-type', r.headers.get('content-type'), 'sample-bytes', len(data))
            txt=data.decode('utf-8','replace')
            print(txt[:500].replace('\n',' ')[:500])
    except Exception as e:
        print('ERROR',type(e).__name__,str(e))
PY  1.0s
  ┊ 💻 $         python3 - <<'PY'
import urllib.request,json,math
UA={'User-Agent':'equityanalysis citation verifier contact@example.com','Accept-Encoding':'identity'}
base='https://data.sec.gov/api/xbrl/companyfacts/CIK0001835632.json'
with urllib.request.urlopen(urllib.request.Request(base, headers=UA), timeout=60) as r:
    cf=json.load(r)
with urllib.request.urlopen(urllib.request.Request('https://data.sec.gov/submissions/CIK0001835632.json', headers=UA), timeout=60) as r:
    sub=json.load(r)
# verify submissions filings labels
recent=sub['filings']['recent']
print('SUBMISSIONS sicDescription:', sub.get('sicDescription'))
for acc in ['0001835632-26-000019','0001835632-26-000011']:
    idx=recent['accessionNumber'].index(acc)
    print('submission', acc, {k: recent[k][idx] for k in ['form','filingDate','reportDate','primaryDocument','primaryDocDescription'] if k in recent})
# concepts expected and entries for accn/date
checks=[
('revenue','us-gaap','RevenueFromContractWithCustomerExcludingAssessedTax','USD'),
('gross_profit','us-gaap','GrossProfit','USD'),
('operating_income','us-gaap','OperatingIncomeLoss','USD'),
('net_income','us-gaap','NetIncomeLoss','USD'),
('cash','us-gaap','CashCashEquivalentsRestrictedCashAndRestrictedCashEquivalents','USD'),
('debt_current','us-gaap','LongTermDebtCurrent','USD'),
('debt_noncurrent','us-gaap','LongTermDebtNoncurrent','USD'),
('shares','dei','EntityCommonStockSharesOutstanding','shares'),
]
for name,tax,concept,unit in checks:
    fact=cf['facts'][tax][concept]
    print('\nCONCEPT',name,tax+':'+concept,'label=',fact.get('label'))
    entries=fact['units'][unit]
    # relevant accns recent
    rel=[e for e in entries if e.get('accn') in ['0001835632-26-000019','0001835632-26-000011']]
    # sort by end/start/fp
    for e in rel:
        if (e.get('filed') in ('2026-05-28','2026-03-11') or e.get('end') in ('2026-05-02','2026-01-31','2026-05-21') or e.get('frame') in ('CY2026Q1','CY2025Q1','CY2025','CY2026Q1I','CY2026Q2I')):
            print({k:e.get(k) for k in ['start','end','val','accn','fy','fp','form','filed','frame'] if k in e})
PY  0.8s
  ┊ 💻 $         python3 - <<'PY'
import json
p='/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json'
d=json.load(open(p))[0]
m=d['metrics']
print('Calculations from structured data:')
qrev=m['revenue']['quarter']['val']
for k in ['gross_profit','operating_income','net_income']:
    q=m[k]['quarter']['val']; a=m[k]['annual']['val']; ttm=m[k]['ttm']
    print(k,'q$',q/1e6,'q margin%',q/qrev*100)
arev=m['revenue']['annual']['val']
for k in ['gross_profit','operating_income','net_income']:
    print(k,'annual margin%',m[k]['annual']['val']/arev*100)
trev=m['revenue']['ttm']
for k in ['gross_profit','operating_income','net_income']:
    calc=m[k]['annual']['val']+m[k]['ytd']['val']-m[k]['ytd_prior']['val']
    print(k,'TTM stored',m[k]['ttm'],'calc',calc,'TTM margin%',m[k]['ttm']/trev*100)
revcalc=m['revenue']['annual']['val']+m['revenue']['ytd']['val']-m['revenue']['ytd_prior']['val']
print('revenue TTM stored/calc',m['revenue']['ttm'], revcalc)
debt=m['debt_current']['val']+m['debt_noncurrent']['val']
net=m['cash']['val']-debt
print('debt calc',debt,'net cash(debt)',net)
price=d['price']['price']; shares=d['shares']['val']
mc=price*shares
ev=mc+debt-m['cash']['val']
print('market cap',mc,'EV',ev,'EV/sales',ev/trev,'EV/opinc',ev/m['operating_income']['ttm'],'P/NI',mc/m['net_income']['ttm'])
print('YoY revenue growth%',(m['revenue']['quarter']['val']/m['revenue']['quarter_prior']['val']-1)*100)
PY  0.1s

╭─ ⚕ Hermes ───────────────────────────────────────────────────────────────────╮
    VERDICT: PASS
    
    Findings:
    - Section 4 source footnote and Section 9 Sources: SEC 10-Q link is valid and fetched successfully (HTTP 200): https://www.sec.gov/Archives/edgar/data/1835632/000183563226000019/mrvl-20260502.htm. SEC submissions metadata confirms accession 0001835632-26-000019, form 10-Q, filingDate 2026-05-28, reportDate 2026-05-02, primaryDocument mrvl-20260502.htm.
    - Section 4 source footnote and Section 9 Sources: SEC 10-K link is valid and fetched successfully (HTTP 200): https://www.sec.gov/Archives/edgar/data/1835632/000183563226000011/mrvl-20260131.htm. SEC submissions metadata confirms accession 0001835632-26-000011, form 10-K, filingDate 2026-03-11, reportDate 2026-01-31, primaryDocument mrvl-20260131.htm.
    - Sections 1 and 3: “Semiconductors & Related Devices” classification is supported by SEC submissions metadata; fetched submissions API shows sicDescription “Semiconductors & Related Devices.”
    - Section 4, “Latest reported quarter revenue”: $2.4B and YoY growth 27.6% match SEC companyfacts / structured data: Q1 revenue 2,417.8M vs prior-year Q1 1,895.3M; calculated growth 27.568%.
    - Section 4, latest quarter margins: gross profit $1.3B / 52.1%, operating income $339.4M / 14.0%, net income $34.5M / 1.4% match structured SEC companyfacts values and calculations.
    - Section 4, latest fiscal year revenue and margins: FY revenue $8.2B, period ended 2026-01-31, gross/operating/net margins 51.0% / 16.1% / 32.6% match 10-K/companyfacts structured values: revenue 8,194.6M; gross profit 4,180.7M; operating income 1,322.9M; net income 2,670.1M.
    - Section 4, TTM revenue / operating income / net income: $8.7B / $1.4B / $2.5B is correctly derived as FY + current YTD - prior-year YTD from SEC companyfacts. Calculated values: revenue 8,717.1M; operating income 1,391.7M; net income 2,526.7M. TTM gross/operating/net margins 51.5% / 16.0% / 29.0% also match calculations.
    - Section 4, cash/debt/net debt: $3.8B cash, $5.0B debt, -$1.1B net cash(debt) match latest 10-Q instant facts and derivation. Cash concept verified in companyfacts as CashCashEquivalentsRestrictedCashAndRestrictedCashEquivalents = 3,843.6M; current long-term debt = 0; noncurrent long-term debt = 4,961.3M; net cash(debt) = 3,843.6M - 4,961.3M = -1,117.7M.
    - Section 5, shares outstanding: 874.8M matches SEC DEI EntityCommonStockSharesOutstanding fact, filed 2026-05-28, end date 2026-05-21.
    - Section 5, market cap / EV / valuation multiples: calculations tie correctly to cited public data and structured SEC inputs. Using share price 290.7900085 and SEC shares 874.8M gives market cap 254.383B; EV = market cap + 4.9613B debt - 3.8436B cash = 255.501B. Multiples match: EV/TTM revenue 29.3x, EV/TTM operating income 183.6x, P/TTM net income 100.7x.
    - Section 9 calculation note is honest: TTM values are described as derived from SEC annual plus current YTD less prior-year YTD facts, and market cap is described as latest close multiplied by SEC DEI shares outstanding. Derived debt/net debt are also described as derived in Section 4.
    
    Corrections needed:
    - None
╰──────────────────────────────────────────────────────────────────────────────╯

Resume this session with:
  hermes --resume 20260603_095001_92352b -p equityanalysis

Session:        20260603_095001_92352b
Duration:       1m 51s
Messages:       16 (1 user, 14 tool calls)
```

### stderr
```

```

## market-and-social-sources
Passed: True
Return code: 0

### stdout
```
Query: You are a fresh context window citation verifier subagent for the MRVL 
equity report.

Files to inspect:
- HTML report: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports
/mrvl-deep-dive-2026-06-03.html
- Structured generation data: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/process
ed/generated_reports_20260603_mrvl.json

Use your tools directly. Do not assume citations are correct just because they 
appear in the report.
Open/read the report and data file. Fetch or inspect cited URLs where possible. 
If a URL is blocked,
record the exact blocker and verify everything still possible from the local 
structured data and URL shape.

Required output format:
VERDICT: PASS or VERDICT: FAIL
Findings:
- concise bullets with exact section/source references
Corrections needed:
- bullets, or "None"

Pass only if the report's citations accurately support the cited claims, source 
labels/dates are honest,
links are valid or accurately described, and calculations are properly tied to 
cited public data.

Role focus: Yahoo market data and social/source provenance.
- Check every citation to Yahoo Finance/chart data and whether the URL/query 
supports the price-history/technical-indicator claims.
- Check cited social/source posts, if present, are used only as provenance for 
why the ticker surfaced and not as proof of business quality.
- Verify cited post links, account labels, and excerpts are represented honestly
from the structured data.

Your task is to check every citation within your role scope.
Initializing agent...
────────────────────────────────────────

  ┊ 🔎 grep      Yahoo|finance.yahoo|chart|price|technical|RSI|moving average|social|tweet|X\b|Twitter|post|Reddit|Stocktwits|source|provenance  0.1s
  ┊ 🔎 grep      Yahoo|finance.yahoo|chart|price|technical|RSI|moving average|social|tweet|X\b|Twitter|post|Reddit|Stocktwits|source|provenance  0.1s
  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html  0.1s
  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json  0.1s
  ┊ 💻 $         python3 - <<'PY'
import json, urllib.request, ssl
url='https://query1.finance.yahoo.com/v8/finance/chart/MRVL?range=1y&interval=1d'
try:
    req=urllib.request.Request(url, headers={'User-Agent':'Mozilla/5.0 citation-verifier'})
    with urllib.request.urlopen(req, timeout=20) as r:
        print('STATUS', r.status)
        print('FINAL_URL', r.geturl())
        print('CONTENT_TYPE', r.headers.get('content-type'))
        data=r.read()
        print('BYTES', len(data))
        j=json.loads(data)
        result=j.get('chart',{}).get('result')
        error=j.get('chart',{}).get('error')
        print('ERROR', error)
        if result:
            res=result[0]
            meta=res.get('meta',{})
            print('META_SYMBOL', meta.get('symbol'))
            print('CURRENCY', meta.get('currency'), 'EXCHANGE', meta.get('exchangeName'), 'RANGE', meta.get('range'), 'INTERVAL', meta.get('dataGranularity'))
            ts=res.get('timestamp') or []
            quote=(res.get('indicators',{}).get('quote') or [{}])[0]
            adj=(res.get('indicators',{}).get('adjclose') or [{}])[0]
            import datetime, zoneinfo
            closes=quote.get('close') or []
            highs=quote.get('high') or []
            lows=quote.get('low') or []
            # print last 5 nonnull rows date close high low adj
            rows=[]
            for i,(t,c) in enumerate(zip(ts,closes)):
                if c is not None:
                    dt=datetime.datetime.fromtimestamp(t, datetime.timezone.utc).strftime('%Y-%m-%d')
                    rows.append((dt,c, highs[i] if i < len(highs) else None, lows[i] if i < len(lows) else None, (adj.get('adjclose') or [None]*len(ts))[i] if i < len(adj.get('adjclose') or []) else None))
            print('NON_NULL_ROWS', len(rows))
            print('LAST_5')
            for row in rows[-5:]: print(row)
except Exception as e:
    print('EXCEPTION', type(e).__name__, repr(e))
PY  0.2s
  ┊ 💻 $         python3 - <<'PY'
from html.parser import HTMLParser
from pathlib import Path
p=Path('/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html')
class P(HTMLParser):
    def handle_starttag(self, tag, attrs):
        if tag=='a':
            print(dict(attrs).get('href'))
P().feed(p.read_text())
PY  0.1s
  ┊ 💻 $         python3 - <<'PY'
import json, urllib.request, datetime, statistics, math
url='https://query1.finance.yahoo.com/v8/finance/chart/MRVL?range=1y&interval=1d'
req=urllib.request.Request(url, headers={'User-Agent':'Mozilla/5.0 citation-verifier'})
j=json.loads(urllib.request.urlopen(req, timeout=20).read())
res=j['chart']['result'][0]
ts=res['timestamp']
q=res['indicators']['quote'][0]
rows=[]
for i,t in enumerate(ts):
    c=q['close'][i]
    if c is not None:
        rows.append({
            'date': datetime.datetime.fromtimestamp(t, datetime.timezone.utc).strftime('%Y-%m-%d'),
            'close': c,
            'high': q['high'][i],
            'low': q['low'][i],
        })
closes=[r['close'] for r in rows]
last=rows[-1]
ma50=sum(closes[-50:])/50
ma200=sum(closes[-200:])/200
change=[closes[i]-closes[i-1] for i in range(1,len(closes))]
last14=change[-14:]
gains=[max(x,0) for x in last14]
losses=[max(-x,0) for x in last14]
avg_gain=sum(gains)/14
avg_loss=sum(losses)/14
rsi=100 if avg_loss==0 else 100-100/(1+avg_gain/avg_loss)
support60=min(r['low'] for r in rows[-60:])
res60=max(r['high'] for r in rows[-60:])
low52=min(r['low'] for r in rows)
high52=max(r['high'] for r in rows)
print('last', last)
print('ma50', ma50, 'round', round(ma50))
print('ma200', ma200, 'round', round(ma200))
print('pct_from_200', (last['close']/ma200-1)*100)
print('rsi_simple_14', rsi)
print('support60', support60, 'resistance60', res60)
print('low52w', low52, 'high52w', high52)
# market cap calc from structured shares
shares=874800000
market_cap=last['close']*shares
ev=market_cap+4961300000-3843600000
print('market_cap', market_cap, market_cap/1e9)
print('ev', ev, ev/1e9)
print('ev_sales', ev/8717100000)
print('ev_op', ev/1391700000)
print('pe', market_cap/2526700000)
PY  0.2s

╭─ ⚕ Hermes ───────────────────────────────────────────────────────────────────╮
    VERDICT: PASS
    
    Findings:
    - HTML section 9, source list, line 30: Yahoo URL https://query1.finance.yahoo.com/v8/finance/chart/MRVL?range=1y&interval=1d was reachable. Fetch returned HTTP 200, JSON content, symbol MRVL, exchange NMS, currency USD, range 1y, interval/data granularity 1d; no blocker.
    - HTML metric strip line 5 and section 5 line 15: latest close $291 / 2026-06-02 is supported by the Yahoo chart response. Fetched last non-null daily row was 2026-06-02 close 290.7900085449219, which rounds to $291.
    - Structured data lines 39-50 match Yahoo-derived price fields: date 2026-06-02, price 290.7900085449219, MA200 100.20875007629394, RSI14 86.56128553006505, support_60 84.19999694824219, resistance_60/high_52w 291.29998779296875, low_52w 61.150001525878906.
    - HTML section 7 lines 22-25: technical claims are supported by recomputation from fetched Yahoo daily OHLC data:
      - 200-day MA = 100.20875007629394, report $100.
      - Price vs 200-day MA = 190.184%, report 190.2%.
      - Simple RSI(14) = 86.5613, report 86.6.
      - 60-day support/resistance = 84.1999969 / 291.2999878, report $84 / $291.
      - 52-week low/high = 61.1500015 / 291.2999878, report $61 / $291.
    - HTML section 5 lines 17-20: market-derived valuation calculations are properly tied to cited public data. Recomputed using Yahoo close 290.7900085449219, SEC shares 874.8M, debt 4.9613B, cash 3.8436B: market cap $254.383B, EV $255.501B, EV/sales 29.31x, EV/operating income 183.59x, P/TTM net income 100.68x, matching report rounding.
    - HTML section 2 line 7 accurately represents source provenance from structured data lines 423-429: selected ticker override pipeline_v2_selected_ticker_smoke, mentions 0, unique accounts 0, source_posts [], and “social evidence intentionally not used as proof of merit.”
    - No cited social/source post links, account labels, or excerpts are present in the report; none required verification. The report uses the selected-ticker provenance only to explain why MRVL surfaced, not as proof of business quality.
    
    Corrections needed:
    - None
╰──────────────────────────────────────────────────────────────────────────────╯

Resume this session with:
  hermes --resume 20260603_095155_5b711c -p equityanalysis

Session:        20260603_095155_5b711c
Duration:       1m 19s
Messages:       14 (1 user, 12 tool calls)
```

### stderr
```

```

## citation-coverage-and-format
Passed: True
Return code: 0

### stdout
```
Query: You are a fresh context window citation verifier subagent for the MRVL 
equity report.

Files to inspect:
- HTML report: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports
/mrvl-deep-dive-2026-06-03.html
- Structured generation data: 
/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/process
ed/generated_reports_20260603_mrvl.json

Use your tools directly. Do not assume citations are correct just because they 
appear in the report.
Open/read the report and data file. Fetch or inspect cited URLs where possible. 
If a URL is blocked,
record the exact blocker and verify everything still possible from the local 
structured data and URL shape.

Required output format:
VERDICT: PASS or VERDICT: FAIL
Findings:
- concise bullets with exact section/source references
Corrections needed:
- bullets, or "None"

Pass only if the report's citations accurately support the cited claims, source 
labels/dates are honest,
links are valid or accurately described, and calculations are properly tied to 
cited public data.

Role focus: citation coverage and citation hygiene.
- Check every citation and source link in the report, including section 9 
Sources and inline source notes.
- Identify specific quantitative or factual claims that should cite 
SEC/Yahoo/social data but do not.
- Confirm citation text is specific enough for a reader to know what source 
supports the claim.
- Confirm links are properly formed HTML anchors and no bare or empty source 
links are presented as evidence.

Your task is to check every citation within your role scope.
Initializing agent...
────────────────────────────────────────

  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html  0.1s
  ┊ 📖 read      /tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/processed/generated_reports_20260603_mrvl.json  0.1s
  ┊ 💻 $         python3 - <<'PY'
from html.parser import HTMLParser
from pathlib import Path
p=Path('/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html')
html=p.read_text()
class P(HTMLParser):
    def __init__(self):
        super().__init__(); self.anchors=[]; self.stack=[]; self.current=None; self.sections=[]; self.cur_section=None; self.text=[]
    def handle_starttag(self, tag, attrs):
        attrs=dict(attrs)
        self.stack.append(tag)
        if tag=='section': self.cur_section={'heading':'','texts':[]}
        if tag=='a': self.current={'href':attrs.get('href'), 'text':''}
    def handle_endtag(self, tag):
        if tag=='a' and self.current:
            self.anchors.append(self.current); self.current=None
        if tag=='section' and self.cur_section:
            self.sections.append(self.cur_section); self.cur_section=None
    def handle_data(self,data):
        if self.current is not None: self.current['text']+=data
        s=' '.join(data.split())
        if s and self.cur_section is not None:
            if self.stack and 'h2' in self.stack:
                self.cur_section['heading'] += (' ' if self.cur_section['heading'] else '') + s
            self.cur_section['texts'].append(s)
    def handle_startendtag(self, tag, attrs): pass
parser=P(); parser.feed(html)
print('HTML length', len(html))
print('Anchors:')
for i,a in enumerate(parser.anchors,1): print(i, repr(a['text']), repr(a['href']))
print('\nSections:')
for s in parser.sections:
    print('\n##',s['heading'])
    txt=' '.join(s['texts'])
    print(txt[:2000])
PY  0.1s
  ┊ 💻 $         python3 - <<'PY'
import json, urllib.request, urllib.error, ssl, time
urls=[
'https://www.sec.gov/Archives/edgar/data/1835632/000183563226000019/mrvl-20260502.htm',
'https://www.sec.gov/Archives/edgar/data/1835632/000183563226000011/mrvl-20260131.htm',
'https://data.sec.gov/api/xbrl/companyfacts/CIK0001835632.json',
'https://data.sec.gov/submissions/CIK0001835632.json',
'https://query1.finance.yahoo.com/v8/finance/chart/MRVL?range=1y&interval=1d',
]
ua='Hermes citation verification equityanalysis contact@example.com'
for url in urls:
    print('\nURL',url)
    req=urllib.request.Request(url, headers={'User-Agent':ua, 'Accept':'application/json,text/html,*/*'})
    try:
        with urllib.request.urlopen(req, timeout=25) as r:
            data=r.read(512)
            print('status', r.status, 'content-type', r.headers.get('content-type'), 'first512', data[:160].decode('utf-8','replace').replace('\n',' ') )
    except Exception as e:
        print('ERROR', type(e).__name__, str(e))
PY  1.0s
  ┊ 💻 $         python3 - <<'PY'
import json, urllib.request, math, statistics, datetime, re
from pathlib import Path
base='/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03'
gen=json.loads(Path(base+'/processed/generated_reports_20260603_mrvl.json').read_text())[0]
ua='Hermes citation verification equityanalysis contact@example.com'
def get_json(url):
    req=urllib.request.Request(url, headers={'User-Agent':ua, 'Accept':'application/json'})
    with urllib.request.urlopen(req, timeout=30) as r:
        return json.loads(r.read())
sub=get_json(gen['submissions_url'])
facts=get_json(gen['facts_url'])
yahoo=get_json('https://query1.finance.yahoo.com/v8/finance/chart/MRVL?range=1y&interval=1d')
print('SEC entity', facts.get('entityName'), 'sub sic', sub.get('sic'), sub.get('sicDescription'), 'ticker(s)', sub.get('tickers'))
# filings recent matching accessions
recent=sub['filings']['recent']
accns=recent['accessionNumber']; forms=recent['form']; dates=recent['filingDate']; docs=recent['primaryDocument']
for label,f in gen['filings'].items():
    if f['accession'] in accns:
        i=accns.index(f['accession'])
        print('filing',label,'found:',forms[i],dates[i],docs[i])
    else: print('filing',label,'NOT found in recent')
# find companyfacts entries matching generated values/accessions
matches=[]
for tax,concepts in facts['facts'].items():
    for concept,obj in concepts.items():
        label=obj.get('label')
        for unit,arr in obj.get('units',{}).items():
            for e in arr:
                for path,name in []: pass
                matches.append((tax,concept,label,unit,e))

def find_val(accn, val, start=None, end=None, form=None, unit_filter=None, tol=0):
    res=[]
    for tax,concept,label,unit,e in matches:
        if unit_filter and unit!=unit_filter: continue
        if e.get('accn')!=accn: continue
        if form and e.get('form')!=form: continue
        if start and e.get('start')!=start: continue
        if end and e.get('end')!=end: continue
        if abs(float(e.get('val'))-float(val))<=tol:
            res.append((tax,concept,label,unit,e))
    return res[:10]
for metric,v in gen['metrics'].items():
    if isinstance(v, dict):
        for k,e in v.items():
            if isinstance(e, dict) and 'val' in e and 'accn' in e:
                res=find_val(e['accn'], e['val'], e.get('start'), e.get('end'), e.get('form'))
                print('metric',metric,k,'val',e['val'],'matches',[(r[0],r[1],r[3]) for r in res[:3]])
for k,e in [('shares',gen['shares'])]:
    res=find_val(e['accn'], e['val'], None, e.get('end'), e.get('form'))
    print('metric',k,'val',e['val'],'matches',[(r[0],r[1],r[3],r[4].get('frame')) for r in res[:5]])
# Yahoo parse latest regular daily close
res=yahoo['chart']['result'][0]
ts=res['timestamp']
quote=res['indicators']['quote'][0]
closes=quote['close']
rows=[]
for t,c in zip(ts,closes):
    if c is not None:
        rows.append((datetime.datetime.utcfromtimestamp(t).date().isoformat(), c))
print('Yahoo meta',res['meta'].get('symbol'),res['meta'].get('regularMarketPrice'),res['meta'].get('regularMarketTime'))
print('last 5 Yahoo closes:', rows[-5:])
print('local price date/value',gen['price']['date'],gen['price']['price'])
# compute calculations from local data
m=gen['metrics']; p=gen['price']; val=gen['valuation']; shares=gen['shares']['val']
calc={
 'yoy_rev': (m['revenue']['quarter']['val']/m['revenue']['quarter_prior']['val']-1)*100,
 'q_gm': m['gross_profit']['quarter']['val']/m['revenue']['quarter']['val']*100,
 'q_om': m['operating_income']['quarter']['val']/m['revenue']['quarter']['val']*100,
 'q_nm': m['net_income']['quarter']['val']/m['revenue']['quarter']['val']*100,
 'fy_gm': m['gross_profit']['annual']['val']/m['revenue']['annual']['val']*100,
 'fy_om': m['operating_income']['annual']['val']/m['revenue']['annual']['val']*100,
 'fy_nm': m['net_income']['annual']['val']/m['revenue']['annual']['val']*100,
 'ttm_rev': m['revenue']['annual']['val']+m['revenue']['ytd']['val']-m['revenue']['ytd_prior']['val'],
 'ttm_gp': m['gross_profit']['annual']['val']+m['gross_profit']['ytd']['val']-m['gross_profit']['ytd_prior']['val'],
 'ttm_oi': m['operating_income']['annual']['val']+m['operating_income']['ytd']['val']-m['operating_income']['ytd_prior']['val'],
 'ttm_ni': m['net_income']['annual']['val']+m['net_income']['ytd']['val']-m['net_income']['ytd_prior']['val'],
 'market_cap': p['price']*shares,
 'debt': m['debt_current']['val']+m['debt_noncurrent']['val'],
 'ev': p['price']*shares + m['debt_current']['val']+m['debt_noncurrent']['val']-m['cash']['val'],
}
calc.update({'ev_sales':calc['ev']/calc['ttm_rev'], 'ev_oi':calc['ev']/calc['ttm_oi'], 'p_ni':calc['market_cap']/calc['ttm_ni'], 'ma50_pct':(p['price']/p['ma50']-1)*100, 'ma200_pct':(p['price']/p['ma200']-1)*100})
print('calculations')
for k,v in calc.items(): print(k, v)
print('reported valuation', val)
PY  1.1s
  ┊ 💻 $         python3 - <<'PY'
import json, urllib.request
from pathlib import Path
base='/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03'
gen=json.loads(Path(base+'/processed/generated_reports_20260603_mrvl.json').read_text())[0]
ua='Hermes citation verification equityanalysis contact@example.com'
def get_json(url):
    req=urllib.request.Request(url, headers={'User-Agent':ua, 'Accept':'application/json'})
    with urllib.request.urlopen(req, timeout=30) as r: return json.loads(r.read())
facts=get_json(gen['facts_url'])
rows=[]
for tax,concepts in facts['facts'].items():
  for concept,obj in concepts.items():
    for unit,arr in obj.get('units',{}).items():
      for e in arr: rows.append((tax,concept,obj.get('label'),unit,e))
for metric in ['cash','assets','liabilities','equity','debt_current','debt_noncurrent']:
    e=gen['metrics'][metric]
    found=[]
    for tax,concept,label,unit,r in rows:
        if r.get('accn')==e['accn'] and r.get('end')==e['end'] and r.get('form')==e['form'] and float(r.get('val'))==float(e['val']):
            found.append((tax,concept,label,unit,r.get('frame')))
    print(metric,e['val'],found[:10])
PY  0.6s
  ┊ 💻 $         python3 - <<'PY'
from pathlib import Path
import re
html=Path('/tmp/equityanalysis-reports-v2/data/pipeline/smoke-tests/mrvl/2026-06-03/reports/mrvl-deep-dive-2026-06-03.html').read_text()
print('empty anchors', re.findall(r'<a\b[^>]*>\s*</a>', html, re.I))
# remove href attrs and anchor text? just list URL strings occurrences
for m in re.finditer(r'https?://[^"\s<>]+', html): print('url string', m.group(0)[:150])
print('href attrs count', len(re.findall(r'href="([^"]*)"', html)))
PY  0.1s

╭─ ⚕ Hermes ───────────────────────────────────────────────────────────────────╮
    VERDICT: PASS
    
    Findings:
    - Section 4 “Financial Snapshot and Quality” source note: all cited SEC links are valid and fetched successfully (HTTP 200): 10-Q filed 2026-05-28, 10-K filed 2026-03-11, SEC companyfacts, SEC submissions metadata.
    - Section 4 SEC filing labels/dates are honest: SEC submissions metadata confirms MRVL CIK 0001835632, SIC “Semiconductors & Related Devices,” 10-Q accession 0001835632-26-000019 filed 2026-05-28, and 10-K accession 0001835632-26-000011 filed 2026-03-11.
    - Section 4 financial values are supported by SEC companyfacts and local structured data:
      - Q1 revenue $2.4178B, prior-year Q1 revenue $1.8953B, YoY growth 27.6% verified.
      - Q1 gross profit $1.2608B / 52.1%, operating income $339.4M / 14.0%, net income $34.5M / 1.4% verified.
      - FY revenue $8.1946B and FY margins 51.0% / 16.1% / 32.6% verified.
      - TTM revenue / operating income / net income of $8.7171B / $1.3917B / $2.5267B verified from FY + current YTD - prior-year YTD.
      - Cash $3.8436B and noncurrent debt $4.9613B verified in companyfacts; derived net debt about $1.1177B matches report rounding to -$1.1B net cash(debt).
    - Section 5 “Valuation and Expected Return”: Yahoo Finance chart API link fetched successfully (HTTP 200) and supports latest close $290.7900085 on 2026-06-02. SEC DEI companyfacts supports 874.8M shares outstanding filed 2026-05-28.
    - Section 5 valuation calculations are properly tied to cited public data and local structured data:
      - Market cap $254.4B = $290.7900085 x 874.8M.
      - EV $255.5B = market cap + $4.9613B debt - $3.8436B cash.
      - EV / TTM sales 29.3x, EV / TTM operating income 183.6x, and P / TTM net income 100.7x verified.
    - Section 7 “Technical Setup / Entry Discipline”: Yahoo chart API supports the cited price history source. Local structured generation data supports price, MA50, MA200, RSI(14), support/resistance, and 52-week range values; derived 89.6% vs 50-day MA and 190.2% vs 200-day MA verified.
    - Section 9 “Sources”: all five source anchors are properly formed HTML anchors with non-empty labels and valid hrefs. No bare or empty source links were found.
    - Section 2 social-signal provenance is accurately represented: structured generation data shows selected ticker override, mentions 0, unique accounts 0, and source_posts empty; report correctly does not present social evidence as investment merit.
    
    Corrections needed:
    - None
╰──────────────────────────────────────────────────────────────────────────────╯

Resume this session with:
  hermes --resume 20260603_095316_c97734 -p equityanalysis

Session:        20260603_095316_c97734
Duration:       2m 24s
Messages:       15 (1 user, 13 tool calls)
```

### stderr
```

```