| name | content-report |
| description | Pull performance data for published content across every surface — LinkedIn, Dev.to, Google Search Console, GA4, and AI citation tracking (Perplexity, Anthropic, OpenAI). Grades each piece as winner, average, or underperformer and surfaces whether an AI search engine has cited it. |
/content-report — The Analytics Lead
Pull performance data for your published content. Cross-references Google Search Console (position, CTR), GA4 (session duration), platform-native stats (LinkedIn impressions, Dev.to views), and AI citation checks (Perplexity, Anthropic, OpenAI web search) to grade each piece.
Preamble
source "$(dirname "$0")/../lib/preamble.sh"
Arguments
Optional:
- --site: Filter by site key (e.g.,
kaicalls, connorgallic, meetkai)
- --all: Show all published content (default if no args)
Example: /content-report --site kaicalls
Example: /content-report
The Skill
Step 1: Refresh Data
Before the report, refresh the data sources you care about. Skip any step where you don't have the API key.
python3 -m scripts.content.tracker_cli pull-devto
python3 -m scripts.content.tracker_cli citations
python3 -m scripts.content.tracker_cli linkedin --id <entry_id> --interactive
python3 -m scripts.content.tracker_cli linkedin --id <entry_id> \
--url https://linkedin.com/pulse/... \
--impressions 1850 --reactions 34 --comments 7 --reshares 2 --dms 3
Step 2: Load Enriched Report
python3 -m scripts.content.tracker_cli report --format json
If no published content is found, tell the user: "No published content in the log. Content is logged automatically when it passes /content-gate."
Step 3: Display Performance Overview
Present the data:
CONTENT PERFORMANCE REPORT
══════════════════════════════════════════
Total pieces: {N}
Winners: {green} {count} ({pct}%)
Average: {yellow} {count} ({pct}%)
Underperformers: {red} {count} ({pct}%)
Pending (< 30d): {gray} {count}
GRADING THRESHOLDS (search surface):
Position ≤ 5 | CTR ≥ 5% | Session ≥ 90s
RECENT CONTENT:
[+] kaicalls-20260316 "AI receptionists" pos:3 CTR:7.2% 91s WINNER li=4.2K/86r/3dm cits=2/4
[+] connor-20260414 "MeetKai audit" — — — PENDING li=1.9K/52r/1dm cits=1/3
[~] kaicalls-20260310 "law firm answering" pos:12 CTR:2.1% 45s AVERAGE devto=320v/12r cits=0/3
[-] abp-20260308 "backyard design" pos:28 CTR:0.4% 22s UNDER li=80/1r cits=0/3
[?] kaicalls-20260322 "virtual receptionist" (pending — 8 days old)
Legend for the compact metric strings:
li=1850/34r/2dm — LinkedIn impressions / reactions / DMsdevto=450v/12r — Dev.to views / reactionscits=2/4 — positive AI citations / total citation checks run
Step 4: Insights
If there are 3+ graded pieces, provide insights:
- Which format performs best (blog vs linkedin vs devto vs email)
- Which persona performs best
- Which hook type performs best (if tracked)
- Average quality gate score of winners vs underperformers
- AI citation patterns — which providers cite our content most often, which queries trigger citations, whether articles with high GSC position also attract AI citations
Example:
INSIGHTS:
Best performing format: linkedin (3/4 winners)
Best performing persona: Shock Absorber (2/2 winners)
Avg gate score winners: 82/100 vs underperformers: 61/100
AI CITATIONS:
Most citing provider: Perplexity (4 citations across 3 articles)
Top-cited article: connor-20260414 — 3 citations
Queries that cite us: "best AI answering service", "Connor Gallic AI",
"answering service alternatives 2026"
Articles never cited: abp-20260308, kaicalls-20260310 → strong GEO-rewrite candidates
Step 5: Recommend Next Actions
Based on the data:
- Pending 30-day review: "3 pieces ready for 30-day review. Performance data will be pulled on next check."
- Underperformers: "Consider revising underperformers or running
/content-retro to extract patterns."
- Missing LinkedIn stats: "N LinkedIn pieces published in the last 14 days have no recorded metrics. Run
kai-tracker linkedin --id <id> --interactive to record them."
- Missing citation checks: "N tracked articles have no
citations-targets.json entries. Use kai-tracker targets --id <id> --add-query '...' to configure."
- No recent content: "No content published in the last 14 days. Run
/content-ideas for topic suggestions."
Data Sources Behind This Skill
| Source | Where it lives | Refreshed by |
|---|
| Publish log | ~/.kai-marketing/content-log.jsonl | /content-gate passes it through on publish |
| Platform metrics (Dev.to, LinkedIn) | ~/.kai-marketing/metrics/{id}.json | kai-tracker pull-devto / kai-tracker linkedin |
| AI citation events | ~/.kai-marketing/citations/{id}.jsonl | kai-tracker citations (cron-compatible) |
| Citation targets | ~/.kai-marketing/citations-targets.json | kai-tracker targets --id <id> --add-query '...' |
| GSC + GA4 grading | Live API calls via scripts/self_improvement/performance_check.py | Invoked automatically by kai-tracker report |
Environment Variables
If a key is missing, the corresponding check is skipped with a warning — the report still runs with whatever data is available.
Error Handling
- No content log: Direct to
/content-write to publish first piece
- GSC/GA4 API unavailable: Show content log with platform/citation data, note "Search surface performance unavailable — showing platform metrics only"
- All AI citation providers missing keys: Skip Step 1's citations call, note in the report "Citation tracking unavailable — set at least one of PERPLEXITY_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY"
Chain State
Reads from: ~/.kai-marketing/content-log.jsonl, ~/.kai-marketing/metrics/, ~/.kai-marketing/citations/
Feeds into: /content-retro (weekly pattern analysis, now including citation patterns)
Scheduling
Recommended cadence for a solo operator:
- On publish:
/content-gate writes to the log automatically
- Weekly:
kai-tracker pull-devto + kai-tracker citations (put in cron or weekly heartbeat)
- Per LinkedIn post, 24h + 7d after publish:
kai-tracker linkedin --id <id> --interactive
- 30 days after publish: the existing performance_check cron handles GSC + GA4 automatically
