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Build decision-tree training in plain language. Describe the scenario, the choice points, and the consequences, your coding agent produces a SCORM-ready branching scenario for any LMS.
A decision-tree training activity where the learner makes choices that change what happens next. Different paths lead to different outcomes, different feedback, and different scores, so the same scenario teaches different lessons depending on how the learner navigates it.
From a plain-English scenario description to a SCORM-ready branching simulation. No flowchart software, no XML, no scripting language.
Tell your coding agent the setup, the stakeholder, and the moment of decision. Your tools generate a coherent first draft of the tree instead of forcing you into a templating UI.
Name the decisions that matter and the consequences of each path. The tool fills in plausible distractor branches and dead-ends so the learner faces real ambiguity.
"Add a stakeholder who pushes back at the midpoint." "Make the easy path more tempting." Iterate by talking with your coding agent, not by clicking through a graph editor.
One command produces a SCORM 1.2 zip. Upload to Cornerstone, Moodle, Canvas, TalentLMS, or any SCORM LMS. Path-level scores post back to the gradebook automatically.
The same toolchain powers sales-decision rehearsal, manager judgment training, compliance dilemmas, clinical decision-making, and ethics scenarios. Describe the choice, the tree builds itself.
Walk reps through pricing pushback, multi-thread navigation, and exec-level objections. Different paths model different deal outcomes.
Performance conversations, layoffs, conflict resolution, the cases without a single right answer. Branching scenarios let managers practice the tradeoffs safely.
Conflict-of-interest moments, gifts-and-entertainment edge cases, data-handling decisions. The branching format forces learners to commit to a choice and see consequences.
Practice triage and treatment-selection decisions with branching consequences, grounded in your clinical guidelines.
Bring history, civics, or biology cases to life as branching choices. Learners discover that the same facts can lead to different defensible decisions.
Simulate outages, recalls, or PR incidents. Branching paths force learners to commit to a sequence and see how early choices compound.
When the scenario ends, the AI scores the path the learner took against the consequence weights you set. Each checkpoint comes back with a justification, evidence pulled from the choice, and a specific tip the learner can act on next time.
Update consequences or weights any time. Re-export the SCORM package and the next attempt grades against the new tree.
Each branch carries its own consequence weight. Learners' total score reflects the path they took, not just whether they reached the end.
Learners can replay to explore alternative paths. Scores from each attempt persist so they can compare outcomes side-by-side.
Reviewers can walk every path without grading. Critical for compliance sign-off, instructional-design QA, and SME review.
Tweak a checkpoint, swap an ending, raise the stakes, or rewrite the consequence rubric, just describe the change in your own words. Your coding agent rebuilds the tree and re-exports the SCORM package without you ever touching a graph editor.
When you're happy, export as a SCORM 1.2 package for your LMS, or use the same HTML bundle standalone.
right-thing-bad-outcome. Tree now has 5 reachable endings.Paste any prompt into your coding agent to get a complete branching scenario as a single self-contained HTML file. Adjust the choices, consequences, or rubric in plain language.
A rep faces a 30% discount ask from a champion on the last day of the quarter. The tree branches on hold-the-line, partial-discount, and creative-terms paths.
Using /branching-scenarios, build a 5-checkpoint scenario: rep facing 30% discount ask on quarter-end. Score on margin, deal close, and CEO sign-off.
A manager has to decide how to handle a senior IC who's missed two quarters of goals but is technically irreplaceable on the current project.
Using /branching-scenarios, build a 6-checkpoint scenario: manager handling senior IC who's missed 2Q goals. Score on candor, project risk, and retention.
A regional director is offered a vendor's box at a major sporting event. The tree branches on accept, decline, escalate-to-legal paths.
Using /branching-scenarios, build a 4-checkpoint G&E scenario: director offered vendor sport-suite. Score on policy, disclosure, and vendor relationship.
A charge nurse decides whether to escalate a borderline-stable patient at shift change. The tree branches on hand-off-as-is, page-attending, transfer-to-step-down.
Using /branching-scenarios, build a 5-checkpoint scenario: charge nurse mid-shift escalation. Score on assessment, handoff quality, and patient safety.
An engineer has a critical bug fix ready at 5pm Friday. The tree branches on deploy-now, deploy-Monday, feature-flag rollout, with cascading consequences.
Using /branching-scenarios, build a 4-checkpoint scenario: critical fix at 5pm Friday. Score on customer impact, on-call burden, and process integrity.
A director has to cut 15% of a team. The tree branches on tenure-based, performance-based, and strategic-skills-based selection paths, each with downstream consequences.
Using /branching-scenarios, build a 7-checkpoint scenario: director picking layoff criteria. Score on fairness, business continuity, and team trust.
Every branching scenario exports as a standards-compliant SCORM 1.2 package. Upload the zip, assign it like any other course activity, and completion plus path-level scores flow back to the gradebook automatically.
cmi.core.score.raw and cmi.core.lesson_statusAuthoring, path grading, LMS compatibility, replayability, model choice, answered directly.
A branching scenario is a decision-tree training activity where the learner's choices change what happens next. Different paths lead to different outcomes, scores, and feedback, so the same scenario teaches different lessons depending on the route a learner takes.
A branching scenario gives learners discrete pre-authored choices at each step, so the tree is fixed and reviewable. A role-play is an open conversation with an AI character that can go anywhere. Branching scenarios are better for compliance-grade auditability; role-plays are better for free-form practice.
You author the scenario in plain language with your coding agent, not by clicking nodes in a graph editor. The tree is stored as a readable text document you can diff and version-control. The AI fills in plausible distractor paths so you don't have to author every dead-end yourself.
Yes. Every scenario exports as a SCORM 1.2 package, which works in Cornerstone, Moodle, Canvas, TalentLMS, Docebo, Brightspace, Absorb, Litmos, and every other SCORM-compliant LMS.
Each branch carries a weight reflecting the consequence of that choice. The learner's total score is the sum of weights along the path they took. Some scenarios use a single pass/fail/partial outcome; others use a richer per-objective rubric.
Yes, that's the point. A well-built scenario has several distinct endings reflecting different decision paths, with explicit per-ending feedback that explains why that path produced that outcome.
The bundles run on whichever frontier model you configure, Claude, GPT, Gemini, or a self-hosted model. Pre-authored choice text is model-independent; only AI-generated distractor branches use the model.
Branching Scenarios is in active development. It will install via your coding agent with a single command, the same way the existing role-play skill works today. Add your email below and we'll let you know the day it ships.