Evidence-first scoring
Each opportunity carries the observations behind the score instead of presenting a mysterious priority number.
From findings to the next best action
A prioritized SEO work queue your agent can actually execute.
SearchSignal converts scattered findings into explicit opportunities with evidence, affected URLs, impact, effort, status, and a verification path—then exposes that queue to the AI environment doing the work.
What changes
A list of issues is not a strategy.
Most SEO products stop at detection. SearchSignal keeps the evidence attached while ranking the work, so the model sees why an action matters, what it depends on, which URLs are involved, and how the result should be checked.
- Rank opportunities by expected impact, effort, confidence, and dependency
- Keep audit, keyword, competitor, ranking, and backlink evidence attached
- Track open, planned, in-progress, shipped, and verified states
- Retrieve the live queue through MCP or authenticated HTTP calls
Capability depth
Evidence the agent can inspect, compare, and use.
SearchSignal preserves enough detail for a person to review the reasoning and enough structure for a model to turn the result into work.
Affected-URL scope
See the exact routes, templates, topic hubs, or lost-link targets involved before the work is assigned.
Implementation contracts
Ask the agent to turn a selected opportunity into files, page edits, dependencies, risks, and acceptance checks.
Status and ownership
Keep the queue useful after research by tracking what is approved, assigned, shipped, and verified.
Fast-win filters
Separate low-effort near-term improvements from larger content, architecture, and authority programs.
Agent retrieval
Use list_opportunities or a workspace pack so the work queue stays current inside Cursor, Claude, and custom agents.
Operating loop
From raw signal to a defensible next action.
Collect current signals
Run the audit, connect Search Console, save keyword research, and pull the competitor or backlink evidence relevant to the project.
Normalize the work
Convert findings into actions with one owner, one scope, one reason, and one measurable definition of done.
Rank the queue
Score impact, effort, confidence, urgency, and dependency so the highest-leverage work rises without hiding uncertainty.
Retrieve in the agent
Ask for the top opportunities, supporting evidence, and an implementation contract for the selected item.
Ship and verify
Apply the change, rerun technical checks, update status, and watch the appropriate search signal over time.
Prompt library
Ask for a result that can move directly into delivery.
The best prompts name the project, request the supporting evidence, and specify the format of the handoff.
“List the three highest-confidence opportunities that can be completed in one working session. Include evidence, affected URLs, and verification steps.”
“Turn opportunity 91 into a repository-aware implementation plan with files, dependencies, acceptance criteria, and rollback notes.”
“Summarize the open opportunity queue by growth upside, risk reduction, and effort. Recommend what to do this week and what to defer.”
“Compare completed opportunities with the latest audit and Search Console window. Mark what is technically verified and what still needs performance time.”
Feature FAQ
What to expect from SEO Opportunities.
Audit issues are observations. Opportunities translate one or more observations into a prioritized action with context, scope, effort, evidence, and a verification path.
Yes. Compatible MCP clients and authenticated HTTP agents can request the current opportunity list or receive a compact workspace briefing that includes the highest-value work.
No. It is a decision aid based on the available evidence and assumptions. Search outcomes depend on implementation quality, competition, crawl and indexing behavior, demand, and time.
The intended workflow supports explicit work states so research remains connected to assignment, delivery, and verification rather than becoming another static report.
Connect once. Ask anywhere.
Give your AI the work queue—not another screenshot.
Create a free workspace, connect the client you already use, and put this capability inside the agent workflow.