IndexMind changelog

Rejecting a planned article now generates one replacement into the week the rejection freed, so the plan keeps its coverage instead of losing a week. The rejection is committed first and is never undone by a replacement that fails.

Generation is bounded by the number of open weeks in a phase. Previously the surplus was written to the phase first week, which put several articles on one week.

After a crawl, any planned article whose title matches an indexable page on the site is marked done with the live URL recorded and labelled as detected by IndexMind. A status set by hand is never overwritten.

The generator now sees what the site already publishes, so it no longer proposes articles that already exist, and can suggest improving an existing page instead of publishing a near duplicate.

Bob now has configurable autonomy levels, risk profiles, schedules, and action routing. Teams can review proposed work, approve safe fixes, and keep agent behavior aligned with each project.

This release closes the loop between measurement and action for executives, operators, and technical teams preparing for GA.

The MCP server exposes project recommendations, visibility queries, sentiment results, narratives, and agent actions to compatible coding tools.

Developers can review fix payloads and update workflow status without leaving the editor context where the implementation happens.

Users can switch between Default, Simple, Developer, and Content views in the dashboard header. Each view keeps the same project data while changing the level of detail and action framing.

The view system helps teams share one source of truth across stakeholders instead of creating separate reports for every role.

Teams can connect ClickUp, map projects to lists, and push report tasks or audience fixes into their delivery workflow.

The integration keeps IndexMind as the system of record while giving operators a familiar work surface for prioritization and follow-through.

The connection supports search performance, URL health, indexation coverage, organic versus AI gaps, and alerting workflows.

Teams can compare where pages earn Google impressions against where those same pages are cited by AI systems.

The sentiment surface tracks positive, neutral, and negative framing across AI answers and highlights sources that influence the narrative.

Teams can see which pages and external references shape brand perception, then prioritize fixes that improve clarity and trust.

Competitor workflows classify rival domains, compare citation patterns, and identify topics where another brand earns more AI answer coverage.

The output helps teams decide which content gaps, positioning gaps, and authority gaps should move first.

The engine compares organic search signals with AI citation evidence so teams can spot pages that deserve better answer-engine coverage.

Content teams can use the gaps to prioritize answer capsules, schema updates, internal links, and topic expansions.

The workflow turns discovered questions, keyword clusters, prompt phrases, and content calendar ideas into a shared planning surface.

Teams can move from query discovery to content action without losing the link between traditional search demand and AI visibility goals.

The gauge gives teams a fast read on the four top-level dimensions that shape AI discoverability and brand perception.

It supports executive reporting while keeping the underlying diagnostic surfaces available for operators who need the details.