Cf Analytics

Content Analytics Dashboard

Track ContentForge production quality, pipeline timing, brand-specific patterns, and compliance trends over configurable time periods with automated insights and alert flags.

Context efficiency

Pipeline phase. Grep before Read for references/, humanization-patterns.json, brand voice profiles. Pass earlier-phase outputs by path + line range, not by reloading. On /contentforge:resume, load only the failed phase's state.

When to Use

Use /contentforge:analytics when you need:

• Quality trend visibility — Are scores improving or declining over time?
• Pipeline performance audit — Which phases are slowest? Where are bottlenecks?
• Brand comparison — Which brands consistently score highest/lowest?
• Content type analysis — Are articles scoring better than whitepapers?
• Compliance monitoring — Citation rates, brand adherence, loop frequency
• Capacity planning — Average throughput for estimating batch timelines

For real-time batch monitoring, use the Progress Tracker (built into /batch-process). For individual content production, use [/contentforge](../contentforge/SKILL.md).

What This Command Does

Loads historical production data from Google Sheets (if connected) or local CSV tracking files, calculates aggregate metrics across configurable dimensions, identifies statistical outliers and concerning trends, generates an ASCII dashboard with actionable recommendations, and flags alerts when performance degrades.

Process Flow:

1. Load Data — Read tracking records from Google Sheets (primary) or local CSV fallback
2. Filter & Parse — Apply time period, brand, content type, and metric focus filters
3. Calculate Aggregates — Average scores, trends, percentiles, phase timing breakdowns
4. Detect Outliers — Flag data points beyond 2.0 standard deviations from mean
5. Generate Insights — Identify patterns, correlations, and improvement opportunities
6. Present Dashboard — Render ASCII analytics display with charts and recommendations
7. Alert Check — Evaluate alert rules and surface any triggered flags

Required Inputs

Optional (all have defaults):

• Time Period — 7 | 30 | 90 days (default: 30)
• Brand Filter — Filter to specific brand (default: all brands)
• Content Type Filter — article | blog | whitepaper | faq | research_paper (default: all types)
• Metric Focus — quality | timing | compliance | citations (default: quality)

How to Use

Default Dashboard (Last 30 Days, All Brands)

/contentforge:analytics

Specific Time Period

/contentforge:analytics --period=90

Brand-Specific Analysis

/contentforge:analytics --brand=AcmeMed --period=30

Content Type Focus

/contentforge:analytics --type=whitepaper --period=90

Metric-Specific Deep Dive

/contentforge:analytics --focus=timing --period=30

Combined Filters

/contentforge:analytics --brand=AcmeMed --type=article --focus=quality --period=90

Data Sources

Primary: Google Sheets Tracking

ContentForge's Output Manager (Phase 8) logs every completed piece to a tracking sheet with these columns:

| Column | Type | Description | |--------|------|-------------| | requirementid | string | Unique content ID (REQ-001) | | title | string | Content title | | brand | string | Brand profile used | | contenttype | enum | article, blog, whitepaper, faq, researchpaper | | wordcount | integer | Final word count | | qualityscore | float | Composite score (0-10) | | contentquality | float | Dimension score (0-10) | | citationintegrity | float | Dimension score (0-10) | | brandcompliance | float | Dimension score (0-10) | | seoperformance | float | Dimension score (0-10) | | readability | float | Dimension score (0-10) | | processingtimemin | float | Total pipeline time in minutes | | phase1time | float | Research phase duration | | phase2time | float | Fact-check phase duration | | phase3time | float | Drafting phase duration | | phase4time | float | Validation phase duration | | phase5time | float | Structuring phase duration | | phase6time | float | SEO phase duration | | phase65time | float | Humanizer phase duration | | phase7time | float | Reviewer phase duration | | phase8time | float | Output phase duration | | loopsused | integer | Total feedback loops triggered | | loopdetails | string | Which loops fired (e.g., "P4>P3 x1, P7>P5 x1") | | citationscount | integer | Number of citations in final output | | brokenlinks | integer | Broken links detected (should be 0) | | completedat | datetime | Completion timestamp | | outputurl | string | Google Drive link to .docx |

Fallback: Local CSV

If Google Sheets is not connected, ContentForge writes tracking data to:

~/.claude-marketing/contentforge-tracking.csv

Same column schema as the Sheets version.

What Happens

Step 1: Data Loading (5-10 seconds)

Loading analytics data...
Source: Google Sheets (ContentForge Tracking)
Records found: 147 total
After filters: 42 records (last 30 days, all brands)
Date range: 2026-01-26 to 2026-02-25

Step 2: Aggregate Calculation

Quality Metrics:

• Mean, median, min, max for composite score and each dimension
• Standard deviation for outlier detection
• Trend direction (improving, stable, declining) via linear regression slope
• Percentile distribution (P25, P50, P75, P90)

Timing Metrics:

• Average total processing time by content type
• Phase-by-phase timing breakdown (mean per phase)
• Slowest phase identification
• Comparison against benchmarks from config/analytics-config.json

Compliance Metrics:

• Average citations per piece
• Citation density (citations per 300 words)
• Average loops per piece
• Loop-free completion rate (% of pieces that passed on first review)
• Brand compliance dimension average

Trend Metrics:

• Rolling 7-day average quality score
• Week-over-week quality change
• Content volume by week

Step 3: Outlier Detection

Flag any record where:

• Quality score is >2.0 standard deviations below the mean
• Processing time is >1.5x the benchmark for its content type
• Loops used >3 (suggests requirement or pipeline issues)
• Any dimension score P3 (hallucination fix): 5 occurrences

P7 > P5 (structure fix): 3 occurrences P7 > P6 (SEO fix): 2 occurrences P7 > P3 (content rewrite): 1 occurrence

Most Common Trigger: Hallucination detection in validation phase (45% of all loops). Primarily affects research papers and whitepapers with high citation density requirements.

ALERTS ---------------------------------------------------------------- [!] QUALITY DECLINE: AgencyCo last 3 pieces scored below 8.0 (7.8, 7.6, 7.9). Review brand profile guardrails.

[!] PHASE SLOWDOWN: Whitepaper Phase 4 (validation) averaging 3.8 min vs. 2.0 min benchmark (1.9x). High citation count driving longer validation.

[i] VOLUME NOTE: Research paper sample size is low (2 pieces). Metrics may not be representative. Need 10+ data points for reliable trends.

IMPROVEMENT RECOMMENDATIONS ----------------------------------------------------------------

1. AgencyCo Brand Review: Update brand profile

(last modified 45 days ago). Recent score decline suggests stale guardrails or terminology changes.

1. Whitepaper Validation: Consider pre-filtering

sources in Phase 1 to reduce Phase 4 validation load. Current avg: 22 sources per whitepaper vs. 15-25 target range.

1. Research Paper Pipeline: High loop frequency

(1.5 avg) suggests tighter Phase 1 research briefs could reduce rework. Consider adding outline approval gate before drafting.

1. Citation Density: Blog citation rate (1 per

380 words) is slightly below target (1 per 300 words). Phase 3 keyword: increase inline citation frequency for blogs.

================================================================ Generated: 2026-02-25 14:30:00 Next suggested review: 2026-03-25 (monthly cadence) ================================================================

### Timing-Focused Dashboard (--focus=timing)

================================================================ CONTENTFORGE TIMING ANALYTICS ================================================================ Period: Last 30 Days | Records: 42 pieces ================================================================

TOTAL PROCESSING TIME DISTRIBUTION ---------------------------------------------------------------- 35 min: ██ 2 pieces (5%)

Average: 26.5 min | Median: 24.8 min P90: 35.2 min (90% of pieces finish within)

TIME BY CONTENT TYPE ---------------------------------------------------------------- Min Avg Max P90 vs Bench Article: 18.2 25.2 32.1 29.5 +0.2 min Blog: 12.4 17.8 24.6 21.3 -0.2 min Whitepaper: 28.5 36.1 44.2 42.0 +1.1 min FAQ: 10.1 14.2 18.3 17.0 -0.8 min Research: 48.1 52.3 56.5 55.8 +12.3 min

PHASE WATERFALL (% of Total Time) ---------------------------------------------------------------- Research: ████████████████ 16% (4.2 min) Fact-Check: ████████████ 12% (3.1 min) Drafting: ██████████████████████ 22% (5.8 min) Validation: █████████ 9% (2.4 min) Structuring: ██████████ 10% (2.7 min) SEO: ███████████ 11% (2.9 min) Humanizer: ██████ 6% (1.6 min) Reviewer: █████████ 10% (2.5 min) Output: █████ 5% (1.3 min)

BOTTLENECK ANALYSIS ---------------------------------------------------------------- Primary Bottleneck: Drafting (22% of time)

• Expected: 18% (per phase weight config)
• Overrun: +4% (+1.0 min above weighted expectation)
• Root Cause: Higher word count targets in recent

batch (avg 2,100 words vs. 1,750 typical)

Secondary Bottleneck: Fact-Check for Whitepapers

• Whitepaper avg: 4.8 min (vs. 3.0 min benchmark)
• Cause: 22 sources avg per whitepaper (high end

of 15-25 range)

THROUGHPUT METRICS ---------------------------------------------------------------- Single Pipeline: 2.3 pieces/hour (avg) Batch (5x): 9.4 pieces/hour (effective) Batch Efficiency: 82% (18% overhead for queue mgmt)

================================================================

### Compliance-Focused Dashboard (--focus=compliance)

================================================================ CONTENTFORGE COMPLIANCE ANALYTICS ================================================================ Period: Last 30 Days | Records: 42 pieces ================================================================

CITATION COMPLIANCE ---------------------------------------------------------------- Avg Citations/Piece: 11.2 Target Range: 5-25 (varies by type) Pieces Meeting Target: 40/42 (95%)

Citation Density (per 300 words): Article: 1.2 (target: 1.0) PASS Blog: 0.8 (target: 1.0) BELOW Whitepaper: 1.4 (target: 1.0) PASS FAQ: 0.9 (target: 1.0) BELOW (marginal)

Broken Links Detected: 0/42 pieces (100% clean) Source Age: 94% within 2-year freshness window

BRAND COMPLIANCE SCORES ---------------------------------------------------------------- Brand Avg Score Min Score Violations AcmeMed: 9.6 8.8 0 TechCorp: 9.0 7.5 1 (terminology) AgencyCo: 8.8 7.0 2 (tone drift) FinanceFirst: 9.4 9.0 0

FEEDBACK LOOP COMPLIANCE ---------------------------------------------------------------- Loop Budget Usage: Avg loops/piece: 0.45 (budget: 5 max) Loop-free rate: 71% Max loops any piece: 3 (within budget) Budget exhaustions: 0 (no human escalations)

Human Review Escalations: 0/42 (0%) Score 1.5x its benchmark time | Medium | | Citation Drop | Citation density drops below content-type minimum | Medium | | Loop Spike | Average loops/piece exceeds 2.0 for any content type | High | | Score Floor | Any piece scores below 5.0 composite | Critical | | Volume Gap | Fewer than 10 data points in analysis window | Info |

Configuration

Analytics behavior is controlled by config/analytics-config.json:

• Quality thresholds (excellent, good, acceptable, needs_review)
• Timing benchmarks per content type
• Alert rule conditions
• Trend analysis parameters (window, min data points, outlier threshold)
• Dashboard defaults (time period, charts to display)
• Score component weights

See [config/analytics-config.json](../../config/analytics-config.json) for full configuration.

Data Privacy

• Analytics operates on aggregate metrics only — no content text is stored or displayed
• Tracking data includes scores, timing, and metadata — never the content body
• All data stays within your Google Sheets or local CSV — no external transmission
• Brand names appear in dashboards but can be anonymized with --anonymize flag

Limitations

• Requires at least 10 data points for meaningful trend analysis (30+ recommended)
• Trend direction (improving/declining) is based on linear regression and can be misleading with high variance
• Phase timing accuracy depends on ContentForge logging completeness
• Cannot retroactively analyze content produced before tracking was enabled
• Google Sheets connection required for cross-session data persistence (CSV is session-local fallback)

Agents Used

None. This skill operates entirely on tracked data — no content generation agents are invoked. It reads from the tracking sheet populated by the Output Manager (Phase 8) of the ContentForge pipeline.

Integration with Other Skills

Data Sources:

• /contentforge — Each completed piece adds a row to the tracking sheet
• /batch-process — Batch completions add multiple rows
• /content-refresh — Refresh completions add versioned rows

Acts On Insights:

• Quality decline detected: Review brand profile, run /brand-setup refresh
• Timing bottleneck found: Adjust phase configuration in config/scoring-thresholds.json
• Citation drop flagged: Update Phase 3 citation density targets

Related Skills

• [/contentforge](../contentforge/SKILL.md) — Full content production pipeline (generates tracking data)
• [/batch-process](../batch-process/SKILL.md) — Parallel content processing (generates batch tracking data)
• [/content-refresh](../content-refresh/SKILL.md) — Content updates (generates refresh tracking data)
• [/contentforge:variants](../cf-variants/SKILL.md) — A/B test variation generation

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Version: 3.4.0 Agents: None (data analysis only) Processing Time: 5-15 seconds (data loading + aggregation) Output: ASCII analytics dashboard with trends, comparisons, alerts, and recommendations

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: indranilbanerjee
• Source: indranilbanerjee/contentforge
• License: MIT
• Homepage: https://indranil.in

Install and usage instructions live in the source repository linked above.