# Scenario Maker > Create, edit, or refine Tough Tongue AI scenarios via the ttai MCP server — outbound callers, demo agents, screeners, and practice roleplay. Classifies the job, loads ttai-agent, then calls ttai:create_scenario or ttai:update_scenario. Use when the user says "create a scenario", "create a voice agent", "build a practice scenario", "edit the scenario", "refine the scenario", "fix the scenario", "the agent said X instead of Y", "it ended the call too early", "make it sound more natural", "I have a call in 30 minutes, help me rehearse", or pastes a brief, transcript, or complaint. - Skill: `tough-tongue/scenario-maker` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add tough-tongue/scenario-maker` - Raw SKILL.md: https://api.skillmd.com/api/skills/tough-tongue/scenario-maker/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tough-tongue (https://skillmd.com/u/tough-tongue) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tough-tongue/scenario-maker --- # Scenario Maker One workflow for **new**, **edit**, and **refine**. Load **ttai-agent** for datastore + scenario shape; load `ttai-agent/features/mcp/` before any `ttai:` call. Do not invent fields; load the tool schema. | Job | Signal | Tool | | ---------- | -------------------------------------------------------- | -------------------------------------------- | | **Create** | No live scenario, or "build / make / rehearse" | `ttai:create_scenario` (no `id`) | | **Edit** | Named scenario, "change X to Y", no failure evidence | `ttai:get_scenario` → `ttai:update_scenario` | | **Refine** | Complaint, transcript, low scores, "too early / robotic" | Evidence → surgical `ttai:update_scenario` | If ambiguous: create when nothing exists to fetch; otherwise fetch first. ## 1. Account context Load `ttai-agent/kb/operating-model.md`. Reuse a current, verified workspace context when supplied by the consumer; otherwise call `ttai:list_organizations` and use `org_id` for team work. The public MCP cannot fetch a user profile or effective platform plan—do not treat `list_subscriptions` as either. ## 2. Create Classify → situation file → draft → validate → create. | Type | AI plays | Load from **ttai-agent** | | -------------------------------- | ------------------------------------------------ | ---------------------------------------------------------- | | Cold call / SDR / outbound phone | Outbound caller | `kb/scenario-recipes/cold-call.md` | | Sales roleplay | Prospect | `kb/scenario-recipes/sales-roleplay.md` | | Coaching | Trainer / mentor | `kb/scenario-recipes/coaching.md` | | Demo | Product demo agent | `kb/scenario-recipes/demo.md` | | Other | Interview, support, negotiation, clone, observer | `model-selection.md` + `control.md` + `ai-instructions.md` | Signals: "AI calls the customer" / SDR / SIP → cold call. "Practice selling" → sales roleplay. "Coach my team" → coaching. "Demo my product" → demo. Always load `kb/scenario-authoring.md`, `model-selection.md`, `control.md`, and `ai-instructions.md`. Load `kb/scenario-recipes/cascade-tts.md` only when the selected stamp is full Cascade. Scripted browser walkthroughs: create first, then **browser-demo-builder**. ### Gather + defaults URLs, transcripts, and other MCP tools beat invented facts. Ask only when the brief is silent: | Question | Default | | ------------------ | ------------------------------------------------------------- | | Language | `en-US` | | External TTS voice | Use a user-supplied or provider-returned ID; never invent one | | Cold-call sub-type | Warm lead | | Coaching pattern | A (Situation-First) | | Public or private | `is_public: true` | ### Draft (`ttai:create_scenario`, no `id`) 1. `name` 2. `ai_model_config` — stamp from the **ttai-agent** `kb/entities/scenario/model-selection.md` situation table (cold call / slides → Landmass `cascade` + Cartesia; sales → Galaxy `medium-stable`; coaching / browser demo → Ocean `medium-stable`). Never author `cascade-01` or invent a `tts_voice_id`. Super-agent requires Landmass. 3. `ai_instructions` — shape from `kb/entities/scenario/ai-instructions.md`; content from the recipe. Specify the full role, reality model, flow, tools, and constraints without padding. Two-beat opening: identity/reason → STOP and wait. One question per turn. 4. `user_instructions`, `rubrik` (correct party), `user_friendly_description` 5. `strategy`, `tools_config`, `session_analysis`, `appearance` 6. `is_recording: true` for voice Fast path: `ttai:generate_scenario` then create. Prefer full authoring for team-run scenarios. ### Create checklist - [ ] `name`, `ai_instructions`; `user_friendly_description` for humans - [ ] `ai_model_config` matches the voice, interaction, and channel contract - [ ] `##` sections; `{{ vars }}` have fallbacks - [ ] Opening lives in FLOW (directive, never quoted). No `welcome_instructions` - [ ] `end_session` registered with `add_to_system_prompt: true` - [ ] Talkative `strategy.silence` (omit = 120s hang up) - [ ] Auto-analysis + auto-submit on - [ ] Rubric evaluates the correct party - [ ] Full Cascade: voice-pipeline + STT blocks. Separate-TTS realtime: `tts_*` only. Native realtime: no TTS/STT sub-fields `ttai:create_scenario` → return `https://app.toughtongueai.com/run/`. Private: mention `ttai:create_scenario_access_token`. ## 3. Edit (no failure evidence) `ttai:get_scenario` (resolve id via `ttai:list_scenarios` if they gave a name). Change only what they asked. Partial `ttai:update_scenario`: `id` + changed fields. Re-fetch to confirm. ## 4. Refine (from evidence) Diagnose → plan → surgical edit → verify. Replace or tighten before adding. Flag the user if `ai_instructions` grows more than ~50 tokens. One issue = one edit. Read [references/runtime-behavior.md](references/runtime-behavior.md) before blaming prompt assembly, tools, conductor, or silence. 1. Fetch the scenario (`ttai:get_scenario`). Read all of `ai_instructions`, plus `strategy`, `tools_config`, `session_analysis`. 2. Evidence: pasted transcript/complaint, or `ttai:list_sessions` → `ttai:get_sessions_batch` → `transcript_url`. Quote the prescribed turn vs what the agent did. Do not translate Hindi/Hinglish. 3. Classify: | Symptom | Fix | | -------------------------------------- | -------------------------------------------------------------------------- | | `end_session` too early / late / never | End-of-call block or `tools_config.tools.end_session` | | Wrong branch / skipped step | FLOW triggers; NEVER skip | | Two questions in one turn / robotic | STYLE — bold one rule; do not add a section | | Revealed AI or spoke a tool name | GUARDRAILS | | ~2 min silence then hang up | Talkative `strategy.silence` | | Wrap-up mid-call | `strategy.conductor.messages` | | Wrong voice / locale | Cascade: `tts_voice_id`. Native: `appearance.voice`. Match `language_code` | | Spoke `{{ firstname }}` | CONTEXT fallback | | Browser click misses | **browser-demo-builder** selector guide | | Robotic / restarting opening | FLOW as a directive | 4. Imperative voice. Bind rules to triggers. Send only `id` + changed fields. For `ai_instructions`, send the full updated string. 5. Re-fetch. Report: **Diagnosis**, **Change**, **Token delta**, reminder that **new sessions only** pick up the edit. ## Pitfalls - Stamp from `model-selection.md` (cold call / slides → Cascade; sales → Galaxy; coaching / browser → Ocean). Do not freestyle from channel alone. - Cold-call rubrics score the **lead**; sales rubrics score the **rep**. - Missing `end_session` timing → never hangs up, or hangs up mid-sentence. - Never embed `TTAI_PAT` in anything you generate. ## Key Files - [../ttai-agent/SKILL.md](../ttai-agent/SKILL.md) — intelligence-layer entry - [../ttai-agent/kb/entities/scenario/model-selection.md](../ttai-agent/kb/entities/scenario/model-selection.md) — stamps - [../ttai-agent/kb/scenario-authoring.md](../ttai-agent/kb/scenario-authoring.md) — quality principles - [references/runtime-behavior.md](references/runtime-behavior.md) — refine from evidence