SEO helpful-content proxy
Use VeracityAPI as an automated proxy for helpfulness before search engines evaluate the page. Agents can catch generic, unspecific, unoriginal writing while it is still cheap to fix.
Business value
- Reduces risk of publishing low-value pages at scale.
- Creates an early warning signal before Search Console data arrives weeks later.
- Prioritizes editor attention toward pages most likely to damage search quality.
Agent job to be done
Act as a helpful-content QA analyst. Decide whether the page demonstrates concrete value, originality, and source/provenance signals for the target query.
format: articleintended_use: publishdomain: SEO helpful content
When to call VeracityAPI
Run before publish, and again before updating already-indexed pages after major rewrites.
What text to submit
Primary content, title, meta description, H1/H2s, intro, key comparison sections, and conclusion. Exclude global nav/sidebar/footer.
Decision policy
- allow: low risk and content_trust_score >= 0.65.
- revise: medium risk or evidence flags generic guidance, thin comparisons, or unsupported claims.
- human_review: high risk on money, safety, health, or product recommendation pages.
- aggregate policy: for section scoring, use the worst section as page risk unless only boilerplate is flagged.
Request template
curl https://api.veracityapi.com/v1/analyze -H "Authorization: Bearer DOC_KEY" -H "Content-Type: application/json" -d '{"type":"text","content":"Paste content here","context":{"format":"article","intended_use":"publish"}}'Automation recipe
- SEO agent generates or updates page.
- Extractor sends unique body sections to VeracityAPI.
- Agent maps evidence spans back to headings and line numbers.
- Revision agent adds firsthand details, named examples, data, screenshots, or sources.
- Page can publish only after score falls below configured threshold.
Evidence spans agents should inspect
- thin comparisons with no concrete differentiators
- generic advice matching thousands of pages
- unsupported best/cheap/safe claims
- absence of examples, data, source links, or firsthand details
Policy pseudocode
if (result.recommended_action === "allow") continueWorkflow(); if (result.recommended_action === "revise") rewriteWith(result.evidence, result.recommended_fixes); if (result.recommended_action === "human_review") queueForHumanReview(result); if (result.recommended_action === "reject") discardOrRebuild();
KPIs to track
- pre-publish block rate
- percentage of pages improved before indexation
- ranking/indexing delta for passed vs failed pages
- organic traffic retained
- helpful-content QA queue size
What can go wrong
- This is not a direct Google classifier.
- Helpful content includes UX, links, reputation, and user satisfaction outside the submitted text.
- Use evidence spans to fix pages; do not chase scores blindly.
Cost and latency notes
Analyze only is $0.005 per 1,000 characters; Analyze + revise with auto_revise=true is $0.010 per 1,000 characters. Both round up to the nearest 1,000 characters. Short captions/emails usually cost $0.005; longer pages or chapters scale linearly by length. Current v0.1 latency is LLM-bound, so batch/concurrent orchestration is recommended for high-volume pipelines.
Agent evaluation checklist
- Does this workflow have a costly failure mode from generic or weak-provenance text?
- Can the agent map evidence spans back to editable source locations?
- Should this workflow fail open, fail closed, or queue human review if VeracityAPI is unavailable?
- Which field drives policy: recommended_action, risk_level, content_trust_score, specificity_risk, or provenance_weakness?
- What local rule should complement the API score?