Competitor PR Finder

python3 -c "
import json
data = json.load(open('/tmp/cprf-pr-raw.json'))
for r in data['results']:
    print(f'\n=== {r[\"competitor\"]} ===')
    for track, tdata in r['tracks'].items():
        print(f'\n--- Track {track.upper()} ---')
        print(f'Query: {tdata[\"query\"]}')
        print(f'Answer: {tdata.get(\"answer\",\"\")[:400]}')
        for item in tdata.get('results', [])[:5]:
            print(f'  Title: {item[\"title\"]}')
            print(f'  URL:   {item[\"url\"]}')
            print(f'  Snippet: {item.get(\"content\",\"\")[:200]}')
"

python3 << 'PYEOF'
import json

patterns = {
    "tier_1_channels": [
        # FILL -- channels appearing in 3+ competitors
        # Each: {"channel_name": str, "channel_url": str, "channel_type": str,
        #        "frequency": int, "found_in_competitors": [str],
        #        "evidence_urls": [str], "story_angles_used": [str],
        #        "journalist_name": "", "journalist_beat": ""}
    ],
    "tier_2_channels": [
        # FILL -- channels appearing in exactly 2 competitors
        # Each: {"channel_name": str, "channel_url": str, "channel_type": str,
        #        "frequency": 2, "found_in_competitors": [str], "evidence_urls": [str],
        #        "story_angles_used": [str]}
    ],
    "tier_3_channels": [
        # FILL -- channels appearing in only 1 competitor (name + URL only)
        # Each: {"channel_name": str, "channel_url": str, "found_in_competitor": str}
    ],
    "data_quality_flags": []
}

json.dump(patterns, open('/tmp/cprf-pr-patterns.json', 'w'), indent=2)
PYEOF

python3 -c "
import json
p = json.load(open('/tmp/cprf-pr-patterns.json'))
print(f'Tier 1 channels: {len(p[\"tier_1_channels\"])}')
for ch in p['tier_1_channels']:
    print(f'  {ch[\"frequency\"]}x {ch[\"channel_name\"]} ({ch[\"channel_type\"]}) -- {ch[\"found_in_competitors\"]}')
print(f'Tier 2 channels: {len(p[\"tier_2_channels\"])}')
print(f'Tier 3 channels: {len(p[\"tier_3_channels\"])}')
"

python3 << 'PYEOF'
import json, os, urllib.request

patterns = json.load(open('/tmp/cprf-pr-patterns.json'))
analysis = json.load(open('/tmp/cprf-product-analysis.json'))
l2 = analysis['industry_taxonomy']['l2']
l3 = analysis['industry_taxonomy']['l3']
tavily_key = os.environ.get('TAVILY_API_KEY', '')

lookup_results = []

for channel in patterns.get('tier_1_channels', [])[:7]:
    name = channel['channel_name']
    ctype = channel['channel_type']

    if ctype == 'editorial':
        query = f'"{name}" journalist reporter writer covers {l2} {l3} startups technology'
    elif ctype == 'podcast':
        query = f'"{name}" podcast host interviewer {l2} {l3} founders'
    else:
        query = f'"{name}" moderator community manager {l2} {l3}'

    payload = json.dumps({
        "api_key": tavily_key,
        "query": query,
        "search_depth": "basic",
        "max_results": 5
    }).encode()

    req = urllib.request.Request(
        'https://api.tavily.com/search',
        data=payload,
        headers={'Content-Type': 'application/json'},
        method='POST'
    )
    try:
        with urllib.request.urlopen(req, timeout=20) as resp:
            data = json.loads(resp.read())
            lookup_results.append({
                'channel': name,
                'channel_type': ctype,
                'query': query,
                'answer': data.get('answer', ''),
                'results': [
                    {'title': r['title'], 'url': r['url'], 'content': r.get('content', '')[:400]}
                    for r in data.get('results', [])[:3]
                ]
            })
            print(f'Journalist lookup -- {name}: {len(data.get("results", []))} results')
    except Exception as e:
        lookup_results.append({
            'channel': name, 'channel_type': ctype,
            'query': query, 'answer': '', 'results': [], 'error': str(e)
        })
        print(f'Journalist lookup -- {name}: FAILED ({e})')

json.dump(lookup_results, open('/tmp/cprf-journalist-results.json', 'w'), indent=2)
print(f'Journalist lookups complete: {len(lookup_results)} channels')
PYEOF

python3 -c "
import json
results = json.load(open('/tmp/cprf-journalist-results.json'))
for r in results:
    print(f'\n=== {r[\"channel\"]} ({r[\"channel_type\"]}) ===')
    print(f'Answer: {r.get(\"answer\",\"\")[:400]}')
    for item in r.get('results', []):
        print(f'  {item[\"title\"]}')
        print(f'  {item.get(\"content\",\"\")[:300]}')
"

python3 << 'PYEOF'
import json

patterns = json.load(open('/tmp/cprf-pr-patterns.json'))

# FILL: update journalist_name and journalist_beat for each tier_1 channel
# journalist_name and journalist_beat come from search snippet text only
# Write "not found in search data" if the snippets don't name a person

# Example:
# patterns['tier_1_channels'][0]['journalist_name'] = 'Ingrid Lunden'
# patterns['tier_1_channels'][0]['journalist_beat'] = 'enterprise software and developer tools'

json.dump(patterns, open('/tmp/cprf-pr-patterns.json', 'w'), indent=2)
print('Journalist data updated.')
for ch in patterns['tier_1_channels']:
    print(f"  {ch['channel_name']}: {ch.get('journalist_name','--')} | {ch.get('journalist_beat','--')}")
PYEOF

python3 -c "
import json

analysis = json.load(open('/tmp/cprf-product-analysis.json'))
patterns = json.load(open('/tmp/cprf-pr-patterns.json'))

print('=== PRODUCT ===')
print(f'Name: {analysis[\"product_name\"]}')
print(f'What it does: {analysis[\"one_line_description\"]}')
print(f'Differentiators:')
for d in analysis['differentiators']:
    print(f'  - {d}')
print(f'ICP: {analysis[\"icp\"]}')
print(f'Geography: {analysis[\"geography_bias\"]}')
print()
print('=== TIER 1 CHANNELS ===')
for ch in patterns['tier_1_channels']:
    print(f'\n{ch[\"channel_name\"]} ({ch[\"channel_type\"]}, freq={ch[\"frequency\"]})')
    print(f'  Found in: {ch[\"found_in_competitors\"]}')
    print(f'  Evidence URLs: {ch[\"evidence_urls\"][:3]}')
    print(f'  Story angles: {ch[\"story_angles_used\"]}')
    print(f'  Journalist: {ch.get(\"journalist_name\",\"not found\")} | {ch.get(\"journalist_beat\",\"\")}')
print()
print('=== TIER 2 CHANNELS ===')
for ch in patterns['tier_2_channels']:
    print(f'  {ch[\"channel_name\"]} ({ch[\"channel_type\"]}) -- found in {ch[\"found_in_competitors\"]}')
"

python3 << 'PYEOF'
import json

result = {
    "product_summary": {
        # FILL from analysis
    },
    "competitors_researched": [],  # FILL: names of confirmed competitors
    "tier_1_deep_dives": [
        # FILL per tier 1 channel:
        # {
        #   "channel_name": str,
        #   "channel_type": str,  # editorial / podcast / community
        #   "frequency": int,
        #   "found_in_competitors": [str],
        #   "evidence_urls": [str],
        #   "channel_overview": str,
        #   "why_they_covered_competitors": str,
        #   "story_angles_used": [str],
        #   "journalist_name": str,
        #   "journalist_beat": str,
        #   "approach_method": str,
        #   "cold_pitch_draft": {"subject": str, "body": str}
        # }
    ],
    "tier_2_channels": [
        # FILL: {channel_name, channel_type, frequency, found_in_competitors, evidence_urls}
    ],
    "tier_3_channels": [
        # FILL: {channel_name, found_in_competitor}
    ],
    "bonus_hooks": [
        # FILL: 3 strings -- pitch angles not used by competitors
    ],
    "data_quality_flags": []
}

json.dump(result, open('/tmp/cprf-final.json', 'w'), indent=2)
print(f'Synthesis written.')
print(f'Tier 1 deep dives: {len(result.get("tier_1_deep_dives", []))}')
print(f'Bonus hooks: {len(result.get("bonus_hooks", []))}')
PYEOF

python3 << 'PYEOF'
import json

result = json.load(open('/tmp/cprf-final.json'))
failures = []

# Check 1: em dashes
full_text = json.dumps(result)
if '—' in full_text:
    result = json.loads(full_text.replace('—', '-'))
    failures.append('Fixed: em dashes replaced with hyphens')

# Check 2: banned words
banned = ['powerful', 'seamless', 'innovative', 'game-changing', 'revolutionize',
          'excited to announce', 'cutting-edge', 'best-in-class', 'world-class',
          'leverage', 'transform', 'disrupt']
for word in banned:
    if word.lower() in json.dumps(result).lower():
        failures.append(f'Warning: banned word "{word}" found in output -- review before presenting')

# Check 3: cold pitch subjects exist
for dd in result.get('tier_1_deep_dives', []):
    pitch = dd.get('cold_pitch_draft', {})
    if not pitch.get('subject') or len(pitch.get('subject', '')) < 10:
        dd['cold_pitch_draft']['subject'] = 'not generated'
        failures.append(f'Fixed: missing subject line for {dd.get("channel_name")}')
    if not pitch.get('body') or len(pitch.get('body', '')) < 50:
        failures.append(f'Warning: very short pitch body for {dd.get("channel_name")}')

# Check 4: bonus hooks count
if len(result.get('bonus_hooks', [])) != 3:
    failures.append(f'Expected 3 bonus hooks, got {len(result.get("bonus_hooks", []))}')

# Check 5: "not found in search data" count
nf_count = json.dumps(result).count('not found in search data')
if nf_count > 0:
    failures.append(f'INFO: {nf_count} field(s) marked "not found in search data" -- verify before outreach')

# Check 6: tier 1 channels have evidence URLs
for ch in result.get('tier_1_deep_dives', []):
    if not ch.get('evidence_urls'):
        failures.append(f'Warning: {ch["channel_name"]} has no evidence_urls')

if 'data_quality_flags' not in result:
    result['data_quality_flags'] = []
result['data_quality_flags'].extend(failures)

json.dump(result, open('/tmp/cprf-final.json', 'w'), indent=2)
print(f'QA complete. {len(failures)} issues addressed.')
for f in failures:
    print(f'  - {f}')
if not failures:
    print('All QA checks passed.')
PYEOF

## PR Intel: [product_name]
Date: [today] | Competitors researched: [N] | Tier 1 channels: [N] | Tier 2 channels: [N]

---

### Your Product
[one_line_description]
Differentiators: [list]
Competitors researched: [names]

---

### Tier 1 Channels (Proven Beats -- Found in 3+ Competitors)

*These channels have already covered multiple companies in your space.*

| Channel | Type | Found in | Journalist/Host | Approach |
|---|---|---|---|---|
[one row per tier 1 channel]

---

### Deep Dives + Cold Pitches

#### 1. [Channel Name] (Tier 1 -- [Type], found in [N] competitors)

Covers: [channel_overview]
Covered competitors: [found_in_competitors with evidence URLs]
Story angle they used: [why_they_covered_competitors]
Journalist/Host: [journalist_name] | Beat: [journalist_beat]
How to reach: [approach_method]

**Cold pitch:**
Subject: [subject]

[body -- 3-4 sentences]

---

[repeat for each tier 1 channel]

---

### Tier 2 Channels (Warm -- Found in 2 Competitors)

| Channel | Type | Found in | URL |
|---|---|---|---|
[one row per tier 2 channel]

---

### Tier 3 Channels (Discovery -- Found in 1 Competitor)

[comma-separated list of channel names with URLs]

---

### 3 Bonus Hooks (Angles Your Competitors Didn't Use)

1. [hook_text]
2. [hook_text]
3. [hook_text]

---
Data notes: [data_quality_flags, or "None"]
Saved to: docs/pr-intel/[PRODUCT_SLUG]-[DATE].md

DATE=$(date +%Y-%m-%d)
OUTPUT_FILE="docs/pr-intel/${PRODUCT_SLUG}-${DATE}.md"
mkdir -p docs/pr-intel
echo "Saved to: $OUTPUT_FILE"

rm -f /tmp/cprf-product-raw.md /tmp/cprf-product-analysis.json \
      /tmp/cprf-competitors-raw.json /tmp/cprf-competitors-confirmed.json \
      /tmp/cprf-pr-raw.json /tmp/cprf-pr-patterns.json \
      /tmp/cprf-journalist-results.json /tmp/cprf-final.json
echo "Temp files cleaned up."