description: "Reference reference guide for content strategy matrices and schemas" version: "1.0"

SEO Strategy Reference — Scripts, Weights & Output Contract

Internal reference for /seo-strategy workflow. This file contains the detailed script commands, weight tables, and output schemas. The main workflow file (seo-strategy.md) references this — do NOT duplicate content.

Strategy Data Collection Scripts

Run these scripts sequentially. All output JSON to {PROJECT_DIR}/data/.

# 1. Content Coverage (25%)
python .agents/scripts/run_plugin_script.py seo-content-gap content_gap_analyzer.py <domain> \
  --competitors comp1,comp2 --json --output-file data/content_gap-{date}.json

# 2. Topical Authority (20%)
python .agents/scripts/run_plugin_script.py seo-topical-authority topical_authority_analyzer.py <domain> \
  --json --output-file data/topical_authority-{date}.json

# 3. Entity Readiness (10%)
python .agents/scripts/run_plugin_script.py seo-entity entity_extractor.py <url> --json --output-file data/entity-{date}.json

# 4. Backlink Opportunity (15%) — null score without data provider
python .agents/scripts/run_plugin_script.py seo-backlink backlink_analyzer.py <domain> \
  --competitors comp1,comp2 --json --output-file data/backlink-{date}.json

# 5. Information Gain (15%) — uses competitors from project.json
python .agents/scripts/run_plugin_script.py seo-information-gain information_gain_analyzer.py \
  analyze <url> --competitors comp1,comp2 --json --output-file data/information_gain-{date}.json

# 6. AI Answer Readiness (10%)
python .agents/scripts/run_plugin_script.py seo-answer answer_analyzer.py <url> --json --output-file data/answer-{date}.json

# 7. Agentic Readiness (5%)
python .agents/scripts/run_plugin_script.py seo-answer agentic_checker.py <url> --json --output-file data/agentic-{date}.json

Synthesizer (after all scripts)

# Windows PowerShell safe encoding pipe:
python .agents/scripts/run_plugin_script.py seo-core strategy_synthesizer.py {PROJECT_DIR}/data/ \
  --goal <goal> --industry <industry> --json | Out-File -Encoding utf8 data/strategy-{date}.json

Delta tracking (if previous strategy exists):

python .agents/scripts/run_plugin_script.py seo-core strategy_synthesizer.py {PROJECT_DIR}/data/ \
  --compare {PROJECT_DIR}/data/strategy-{prev_date}.json --json | Out-File -Encoding utf8 data/strategy-delta-{date}.json

Weight Table

Category	Script	Base Weight
Content Coverage	`content_gap_analyzer.py`	25%
Topical Authority	`topical_authority_analyzer.py`	20%
Backlink Opportunity	`backlink_analyzer.py`	15%
Information Gain	`information_gain_analyzer.py`	15%
Entity Readiness	`entity_extractor.py`	10%
AI Answer Readiness	`answer_analyzer.py`	10%
Agentic Readiness	`agentic_checker.py`	5%

If any category is unavailable → weights auto-redistribute proportionally.

Goal & Industry Adjustments

Flag	Effect
`--goal traffic`	Content 30%, Topical 25%
`--goal leads`	Content 20%, Entity 15%
`--goal ai_visibility`	AI Answer 20%, Agentic 10%, IG 20%
`--industry saas`	Topical 25%, Content 20%
`--industry ecommerce`	Backlink 20%, Content 20%
`--industry publisher`	Content 30%, IG 20%

Strategy Score Output Schema

{
  "domain": "example.com",
  "strategy_score": 62,
  "timestamp": "2026-05-14T...",
  "category_scores": {
    "content_coverage": {"score": 55, "weight": 0.25, "source_file": "..."},
    "topical_authority": {"score": 70, "weight": 0.20, "source_file": "..."}
  },
  "weights_used": {"content_coverage": 0.25, ...},
  "priority_matrix": [
    {"category": "...", "score": 55, "gap": 45, "impact": "high", "effort": "medium", "priority": 1}
  ],
  "key_findings": [
    {"category": "...", "finding": "23 missing topics vs competitors", "severity": "high"}
  ],
  "categories_available": ["..."],
  "categories_missing": ["..."],
  "comparison": null
}

Conditional Skills (AI-only analysis, not scripted)

#	Skill	Condition	AI Action
S1	`seo-authority`	Always	Analyze cross-platform presence from entity + backlink data
S2	`seo-social`	VN market	Audit Zalo OA, Mini App SEO-to-Social loops
S3	`seo-coccoc-optimizer`	VN market	Check Hộp trả lời AI, dialect coverage
S4	`seo-competitor-pages`	Always	Generate comparison page templates
S5	`seo-prompt-research`	Research data exists	Feed AI prompt patterns from `/seo-research`
S6	`seo-programmatic`	Data-driven site	Assess pSEO template opportunities

These are handled by AI interpretation, not Python scripts.

Project Run Entry Example

{
  "date": "2026-05-14",
  "type": "strategy",
  "phase": "strategized",
  "score": 62,
  "category_scores": {
    "content_coverage": 55, "topical_authority": 70,
    "backlink_opportunity": null, "information_gain": 48,
    "entity_readiness": 65, "ai_answer_readiness": 42,
    "agentic_readiness": 30
  },
  "report": "reports/strategy-2026-05-14.md",
  "data": "data/strategy-2026-05-14.json"
}