> ## Documentation Index > Fetch the complete documentation index at: https://docs.goparlay.io/llms.txt > Use this file to discover all available pages before exploring further. # Examples > Paste-ready prompts that demonstrate real Parlay workflows. Each prompt below is one paragraph you can paste into Claude Desktop, Cursor, or any MCP-enabled client. Replace `demo-acme` / `alex-smith` with your own org / rep ids. ## Verify connectivity ``` Use parlay tools to ping the server and tell me which environment I'm connected to. ``` Expected: `echo_ping` returns `{ pong: true, key_environment: "sandbox", ... }` in under a second. *** ## The hero workflow — analyze, classify, coach ``` For org "demo-acme" rep "alex-smith", submit mock://perfect-pitch and mock://average-pitch for analysis in parallel. Once both are done, assign Alex's sales persona using both calls. Then ask Scout what Alex's biggest improvement area is and give me a 4-sentence executive summary. ``` What it exercises: parallel async tool calls, persona meta-analysis, Scout multi-turn chat. \~60 seconds end to end. **This is the demo to show stakeholders.** *** ## Coach a single rep ``` Generate a full coaching synthesis for rep alex-smith in org demo-acme using the most recent 5 analyses. Show me the double-down, top gaps, and this-week action plan. ``` What it exercises: `generate_rep_synthesis` with `lookback_count=5` → returns synthesis with action plan citing specific calls. *** ## Tag outcomes for win/loss analysis ``` For analysis , tag it as "sold" with deal amount $45,000 and note "closed on second call". Then list every sold deal in demo-acme this quarter and sum the total pipeline. ``` What it exercises: `tag_disposition`, `list_dispositions` with date range. RevOps-flavored use case. *** ## AI-generate a playbook from raw notes ``` For org "demo-acme", upload two playbook source materials: 1) Title "Top performer highlights" — content: "Our best reps ALWAYS confirm decision-maker authority before a demo. They reframe price objections as ROI questions: 'What would solving this be worth in the next 12 months?' They never send long follow-up emails — they book a 15-minute specific follow-up call instead." 2) Title "Closing patterns" — content: "Top reps use trial closes mid-call: 'If this worked perfectly, would it make sense to move forward?' They create urgency with deadlines tied to business outcomes, not artificial discounts. They always end calls with a specific next step booked on the calendar." Then generate a playbook draft from both source materials. Show me the first 500 characters of the generated content, and publish it as the org's active playbook. ``` What it exercises: `upload_playbook_source` (×2), `generate_playbook_draft` (async, \~20s), `publish_playbook_draft`. The wow moment. *** ## Configure custom scoring criteria ``` Create three custom prompts for demo-acme: 1) Title "Decision-maker confirmation", content "Did the rep confirm the name of the decision-maker before proposing a close?" 2) Title "Budget discovery", content "Did the rep ask about budget authority?" 3) Title "Next-step booking", content "Did the rep book a specific follow-up meeting before ending the call?" All scoring_criterion type. Then list them ordered. ``` What it exercises: `create_custom_prompt` (×3), `list_custom_prompts`. Sales-leader admin flow. *** ## Reorder prompts after creation ``` List the custom prompts for demo-acme. Then reorder them so "Decision-maker confirmation" is first and "Budget discovery" is second. ``` What it exercises: `list_custom_prompts` then `reorder_custom_prompts` with the right ids array. Tests model's ability to chain identifiers. *** ## Quick rep snapshot ``` Show me alex-smith's stats in demo-acme for the last 30 days — overall average, per-pillar scores, and the weekly trend. Then tell me which pillar is trending most. ``` What it exercises: `get_rep_stats` with custom window + interpretation by the model. *** ## Manual persona override ``` Set alex-smith's persona to "challenger" in demo-acme with justification "veteran seller, AI-assigned hard_worker doesn't reflect 8 years of enterprise experience". Then fetch it back to confirm. ``` What it exercises: `set_rep_persona_manually`, `get_rep_persona`. Appends to history with `source: "manual"`. *** ## Scout deep-dive on a single call ``` For analysis , get the welcome questions, then ask the first one and follow up with "what specifically should I have done differently in the moment?" ``` What it exercises: `get_scout_welcome_questions`, `ask_scout_about_call` (multi-turn — Scout remembers turn 1 in turn 2). *** ## Audit configuration ``` Show me everything about demo-acme: org details, all reps, active playbook, all custom prompts, and the latest org insights. ``` What it exercises: `get_org`, `list_reps`, `list_playbooks active_only=true`, `list_custom_prompts`, `get_latest_org_insights` (Phase F). Tests parallel-call orchestration. *** ## Generate an org-level insights snapshot ``` For org "demo-acme", generate an org-level insights snapshot covering the last 30 days. When it's done, summarize the executive_summary and tell me who the top performer is. ``` What it exercises: `generate_org_insights` (async, \~30–60s, \~$0.02–$0.05), then the model parses the snapshot. Sales-leader monthly-review use case. *** ## Leaderboard — pure SQL, no AI cost ``` Show me the top 5 reps in demo-acme by score this month, then by improvement, then by volume. Tell me who appears on multiple lists. ``` What it exercises: `get_leaderboard` called three times with different `sort_by` values, then cross-referenced. No AI cost — pure SQL. *** ## Set up + test a webhook ``` Register a webhook at https://my-app.com/parlay-webhook for analysis.completed and analysis.failed events. Show me the signing_secret. Then send a test event to confirm my endpoint receives it. ``` What it exercises: `register_webhook` (signing\_secret returned ONCE), `test_webhook`. After this, `rotate_webhook_secret` is the only way to ever get a new secret. *** ## Rotate a leaked webhook secret ``` The signing secret for webhook abc-123 was leaked. Rotate it and give me the new secret. Tell me what I need to do on my endpoint to avoid a verification gap. ``` What it exercises: `rotate_webhook_secret`. The model should also explain to update the verification code FIRST, then rotate, since the old secret stops working immediately. *** ## Discoverability — "what can you do?" ``` What tools do you have available from the Parlay MCP server? Group them by category and tell me which ones cost money to run vs which are free. ``` The model will list all 60 tools grouped by domain, and (because every tool description has a cost callout) it'll correctly tag the AI-cost ones. *** ## Cleanup after demo ``` Archive the org demo-acme. ``` Soft-deletes the entire demo workspace. Reversible manually server-side.