{"schema_version":"2.0","record_type":"article","canonical_url":"https://marketingwiki.ai/articles/evidence-backed-content-agent","id":"evidence-backed-content-agent","slug":"evidence-backed-content-agent","title":"Build an Evidence-Backed Content Agent","description":"A research-to-pull-request workflow for producing useful marketing content without hallucinated claims or scaled-content sludge.","dek":"Separate opportunity discovery, research, drafting, verification, and publishing. Give each stage evidence and stop rules.","category":"Workflows","topics":["content operations","research","SEO"],"publishedAt":"2026-08-10","updatedAt":"2026-08-11","lastVerifiedAt":"2026-08-11","readingMinutes":3,"author":"Marketing Wiki Editors","reviewer":"Marketing Wiki Editors","featured":true,"sources":[{"title":"Google guidance on generative AI content","url":"https://developers.google.com/search/docs/fundamentals/using-gen-ai-content"},{"title":"Google spam policies","url":"https://developers.google.com/search/docs/essentials/spam-policies"}],"wordCount":567,"body":"Reliable content automation separates research from writing and publishing. Agent should prepare evidence-backed changes, then open a pull request for human review.\n\nThis article explains architecture and editorial reasoning. Use [executable content-agent workflow](/workflows/evidence-backed-content-agent) to run process, or [index record](/index/evidence-backed-content-agent) for compact machine-readable definition.\n\nGoogle permits AI-assisted content, but warns that generating many pages without added user value can violate scaled-content policy. Production system therefore needs rejection rules, not only writing prompts.\n\n## Pipeline\n\n```text\nOpportunity\n→ approved brief\n→ evidence map\n→ draft\n→ claim verification\n→ editorial review\n→ SEO/AEO review\n→ pull request\n→ human approval\n```\n\nEach stage produces an artifact another stage can inspect.\n\n## 1. Opportunity\n\nOpportunity record should answer:\n\n- Which reader problem exists?\n- Which query or task expresses it?\n- What current pages fail to provide?\n- What original asset can this page add?\n- Which existing page might it duplicate?\n\nReject opportunities based only on keyword variation. \"Best AI email tools for startups\" and \"best AI email tools for small companies\" may describe same decision.\n\n## 2. Brief\n\nApproved brief defines scope before research expands:\n\n```yaml\nprimary_intent: choose architecture for repeatable AI marketing work\nreader: marketer building first repository-based workflow\nrequired_asset: runnable folder structure and approval model\nmust_answer:\n  - when to use prompt, skill, workflow, or agent\n  - where evidence lives\n  - who can publish\nexclusions:\n  - unsupported performance claims\n  - vendor rankings\n```\n\n## 3. Evidence map\n\nResearch agent records claims before prose:\n\n| Claim | Source | Source type | Accessed | Status |\n| --- | --- | --- | --- | --- |\n| GitHub Actions runs repository workflows | GitHub Docs | Primary | 2026-08-10 | Supported |\n| AI content always ranks worse | None | Unsupported | 2026-08-10 | Reject |\n\nSource type matters. Vendor documentation supports what vendor says product does. It does not equal independent performance testing.\n\n## 4. Draft\n\nWriting agent receives approved brief and evidence map. It should not browse new sources during drafting because hidden research makes verification harder.\n\nDraft requirements:\n\n- Direct answer near top\n- One distinct reader intent\n- Original template, example, test, or method\n- Source links near claims\n- Clear uncertainty\n- No invented quotes, numbers, or product behavior\n\n## 5. Verification\n\nVerification agent checks every factual sentence against evidence map.\n\nPossible outcomes:\n\n- Supported\n- Vendor-documented\n- Inferred\n- Stale\n- Contradicted\n- Unsupported\n\nUnsupported claim gets removed or returned to research. Writer cannot quietly soften it into vague wording.\n\n## 6. SEO and answer review\n\nReview technical basics:\n\n- Stable canonical URL\n- Useful title and description\n- Clear headings\n- Crawlable links\n- Internal topic relationships\n- Structured data matching visible page\n- Accurate publication and update dates\n- Short direct answer for question-led pages\n\nNo special markup guarantees inclusion in an AI answer. Strong source clarity and useful page structure improve machine retrieval without pretending to control third-party systems.\n\n## 7. Pull request\n\nAgent opens one focused pull request containing:\n\n- Article\n- Evidence map\n- Related-link updates\n- Generated index changes\n- Validation report\n\nReviewer sees what changed and why. Agent cannot merge its own work.\n\n## Publish gate\n\nPublish only when page passes five tests:\n\n1. Distinct intent\n2. Verified factual claims\n3. Original value beyond source summaries\n4. Relevant internal relationships\n5. Named human approval\n\nProduction volume should follow passing pages, not precede them."}