Bugbot effort levels in Cursor

The situation

Counter-thesis: the best review setting is not always the fastest one; in Cursor, the right Bugbot effort level is the one your team can repeat.

The wrong path: I believed review automation was a single switch. I tried to leave it on Default everywhere, and here is what happened: routine diffs moved quickly, risky diffs got the same treatment, and the team started treating the setting like background noise instead of a decision.

Diagnosis: this is the old trap of one-size-fits-all automation, the same pattern that shows up whenever a control surface is easier to set than to govern. I also think of it as a version of Goodhart’s law: once the setting becomes the goal, the workflow stops serving the work.

The actual thesis: Cursor’s Bugbot effort levels are a workflow control, not just a quality knob.

That thesis matters for Cursor engineering teams because the same review policy has to survive subagents, skills, custom agents, and shared team rules. If you are building a workshop or rollout plan, the question is not “what is the strongest setting?” but “what setting can we repeat across the team?”

Walkthrough

Failure mode: you leave every PR on Default and call it policy. If you shipped AI code you have hit this: the team wants consistency, but the review surface is not equally risky. Cursor says Default keeps the same effort level as today and is optimized for efficiency and speed, while High spends more time reasoning. The fix is Risk-Tiered Effort: use Default for low-risk refactors and High for migrations, auth, billing, or anything that crosses service boundaries. That keeps latency low where it should be and reserves deeper review for the diffs that need it. That is tip one.

Failure mode: you assume “more bugs found” always means “better.” If you shipped AI code you have hit this too: the dashboard looks better, but the queue gets slower and people start ignoring the tool when it feels heavy. Cursor says High effort finds more bugs on average than Default, but it also costs more and takes longer. The fix is Budgeted High-Effort Escalation: define a narrow set of PR labels or file patterns that earn High effort, then review the spend weekly. The thesis stays the same: the right Bugbot effort level is the one your team can repeat. That is tip two.

Failure mode: you write vague custom instructions and expect deterministic behavior. If you shipped AI code you have hit this when “use high effort when needed” sounds clear to humans and mushy to agents. Cursor’s Custom mode accepts natural language instructions that dynamically set effort levels, which is useful and easy to overfit. The fix is Decision-Rule Prompting: write the instruction as a boundary, not a vibe. For example:

# Bugbot effort policy
- Use Default for docs, tests, formatting, and small internal refactors.
- Use High for auth, payments, data migrations, concurrency, or any PR touching more than 3 modules.
- If the diff changes public behavior or a rollback path, prefer High.
- If the PR is under 50 lines and only updates comments or copy, stay on Default.

That gives the team something to audit, tune, and explain without guessing what “important” meant last Tuesday. The right Bugbot effort level is the one your team can repeat, and this is how you make it repeatable. That is tip three.

Failure mode: you customize effort without a billing and ownership rule. If you shipped AI code you have hit this when the tool works, then someone asks why the bill moved. Cursor is explicit that customers must be on usage-based billing for Bugbot customization. The fix is Billing-Gated Adoption: document who can enable custom effort, who reviews spend, and what signal triggers rollback to Default. That keeps the thesis honest: the right Bugbot effort level is the one your team can repeat, not the one that surprises finance. That is tip four.

Failure mode: you treat Bugbot as isolated from the rest of Cursor’s team workflow. If you shipped AI code you have hit this when review settings drift because rules live in one place, agent behavior in another, and team conventions nowhere durable. Cursor’s broader model points toward layered rules and team workflows, so connect Bugbot policy to the same governance surface you use for Cursor rules, subagents, and shared conventions. The fix is One Policy, Many Surfaces: keep the effort policy in a reviewable team artifact, then mirror the same intent in your Cursor rules and repository conventions. A practical starter is a short AGENTS.md boundary plus a Cursor review checklist:

## PR review checklist
- Does this PR touch a high-risk area?
- If yes, was Bugbot set to High or custom escalation?
- Is the custom instruction specific enough to audit?
- Is usage-based billing enabled for this workflow?
- Did the reviewer confirm the setting matches the diff risk?

Once that exists, Bugbot stops being a hidden preference and becomes part of the team’s review contract. The right Bugbot effort level is the one your team can repeat, because the policy is visible in the same place your Cursor workflow already lives. That is tip five.

Synthesis: tune effort to risk, not habit. In Slack terms: “Default for routine diffs, High for risky diffs, Custom only when the rule is written down.”

Tradeoffs and limits

Bugbot’s higher effort is not free, and Cursor says so plainly: more reasoning means more cost and more latency. The changelog also does not claim High effort will catch every bug, only that it finds more on average, so treat the setting as probabilistic.

Custom instructions are only as good as the policy text you write. If the rule is vague, the behavior will be harder to predict, which is why the first version should stay short and reviewable.

For Cursor teams, the practical limit is governance bandwidth. If you are already rolling out subagents, skills, or custom agents, do not add a second policy language unless it maps cleanly to the same review surface. That is where our methodology helps: verify the control against a small set of real PRs before broad rollout.

Further reading

• https://cursor.com/changelog
• https://cursor.com/docs
• https://cursor.com/docs/rules
• https://cursor.com/docs/agent
• https://cursor.com/docs/skills
• https://cursor.com/docs/agents-md
• https://cursor.com/docs/team-rules
• https://cursor.com/docs/custom-agents
• https://cursor.com/docs/custom-subagents
• https://cursor.com/docs/background-agents
• https://cursor.com/docs/plan-mode
• https://cursor.com/docs/hooks
• https://cursor.com/docs/workspace-index
• https://cursor.com/docs/notepads
• /topics/subagents-and-skills

Where to go next

Start with one team-owned review policy and one high-risk PR class. Then connect that policy to your Cursor rules and subagents and skills page so the setting is visible, reviewable, and repeatable.