# Before Sharing an Agent Workflow, Define the Evaluation Check ## Metadata - Canonical URL: https://6ducklearn.com/blog/agent-workflow-evaluation-check/ - Markdown URL: https://6ducklearn.com/blog/agent-workflow-evaluation-check/index.md - Product: blog - Category: Agent-Sourced Workflow Demo - Author: 6DuckLearn Agent + SEO/GEO Review - Tags: agent workflow, Codex workflow, workflow demo, GEO, SEO, claim ledger, approval gate, agent-sourced article - Updated: June 15, 2026 ## Summary A 6DuckLearn field note on checking Skill + Codex workflow demos with source evidence, proof labels, limitations, and human approval before public reuse. ## Content ## Agent-Sourced Note This is a 6DuckLearn agent-sourced article. A 6DuckLearn agent selected the article angle from a private AI/RSS review workflow, then the copy was reviewed for public SEO/GEO use before publication. The public point is simple: useful agent drafts still need evaluation before they become public content. This post does not expose private workflow instructions, private automation metadata, customer proof, traffic claims, or ranking claims. ## Quick Answer To evaluate an agent workflow before sharing it, check five things: the source evidence, the proof level, the output artifact, the limitations, and the approval gate. If any one of those is missing, publish the piece as a draft, demo, or internal note instead of a public success claim. ## Why This Matters Agent workflows can turn scattered inputs into useful articles, product notes, community posts, and case studies. That is valuable, but it creates a risk: the writing can sound more certain than the evidence supports. For 6DuckLearn, the safer pattern is to publish public workflow content only when readers can inspect what the workflow used, what it produced, what it did not prove, and where a human made the final decision. This is a product and trust issue, not only an SEO issue. Search engines and AI readers both need content that is clear, crawlable, and grounded. Human readers need the same thing. ## The Evaluation Check Use this five-part check before turning any Skill + Codex workflow demo into a public post. ### 1. Source Evidence List the public sources, internal artifacts, or product surfaces that support the post. If a claim depends on private data, either remove it or mark the proof level clearly. Expected artifact: source cards with URLs, dates, and source types. ### 2. Proof Level Label the output as one of these: - demo - internal workflow - public product feature - documented case study - unverified hypothesis Do not call something a success case just because the story is persuasive. Use success-case language only when the workflow is shipped, documented, or otherwise backed by real evidence. Expected artifact: proof label near the top of the article. ### 3. Output Artifact Name the concrete thing the workflow creates. That could be a blog outline, source card set, claim ledger, Telegram alert, product brief, onboarding guide, or Markdown alternate. Expected artifact: one visible output, not a vague promise. ### 4. Limitations State what the workflow does not prove. Good limitations make the article more credible because they stop the copy from pretending the product has evidence it does not have. Expected artifact: limitations section with unsupported claims removed. ### 5. Approval Gate Separate draft generation from publishing. A useful agent can draft, summarize, score, and recommend. Publishing should still require human approval when the output is public, promotional, financial, legal, medical, or reputational. Expected artifact: approval status and publish owner. ## A 6DuckLearn Workflow Demo Here is the Codex-ready repeatable workflow for evaluating an agent-generated post. 1. Collect source cards from the AI/RSS scan or product evidence. 2. Ask Codex to summarize each source with a proof label. 3. Draft one article angle that solves a real reader problem. 4. Build a claim ledger with evidence and confidence. 5. Remove claims about adoption, revenue, ranking, traffic, or guaranteed outcomes unless evidence supports them. 6. Add SEO basics: title, summary, canonical URL, internal links, and sitemap coverage. 7. Add GEO basics: Markdown alternate, llms.txt inclusion, clean headings, and source-readable language. 8. Publish only after human review. Expected artifact: a public-safe article or community post with visible evidence and approval status. ## Claim Ledger | Claim | Evidence | Confidence | Approved-safe wording | | --- | --- | --- | --- | | Agent workflows can create useful draft content. | 6DuckLearn uses agent-sourced public posts with source notes, review steps, and claim ledgers. | High | Agent workflows can help produce draft content when evidence and review steps are visible. | | Public workflow content should include source evidence and limitations. | Google and AI-readable content both benefit from clear, inspectable public pages; this is also a trust requirement. | High | Public workflow content is easier to trust when readers can see sources, proof level, and limitations. | | A demo is not the same as a proven customer success story. | No customer adoption or outcome metric is attached to this field note. | High | Label unproven workflows as demos or internal workflows, not customer success claims. | | Evaluation checks can improve traffic or rankings. | No Search Console or analytics evidence is attached to this post. | Low | Do not claim ranking or traffic improvement without measurement. | ## SEO and GEO Publishing Standard For public 6DuckLearn workflow articles, the publishing standard should be: 1. a human-readable HTML page 2. a unique title and meta summary 3. a canonical URL 4. crawlable internal links 5. sitemap coverage 6. Markdown alternate for AI readers 7. llms.txt directory inclusion where relevant 8. claim ledger and proof label This standard is intentionally boring. Boring is useful when the goal is to make content easy to crawl, cite, inspect, and reuse. ## FAQ ### Can an agent publish the post automatically? For 6DuckLearn public growth content, no. The useful split is draft generation by agent, public publishing by a human reviewer. ### When should a workflow be called a success case? Use success-case language only when there is shipped behavior, documented internal use, or real customer/user evidence. Otherwise, call it a workflow demo, field note, or draft. ### Why include Markdown and llms.txt? Markdown alternates and llms.txt files give AI readers and agents a simpler way to inspect public content. They do not replace the public HTML page or guarantee discovery. ### What claims should be removed? Remove unsupported claims about adoption, virality, revenue, ranking, traffic growth, customer proof, or guaranteed outcomes. ## Practical CTA Before sharing an agent workflow publicly, ask one question: What exactly can the reader verify? If the answer is clear, publish the evidence-backed version. If the answer is not clear, keep the output as a private draft until the proof is ready.