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--- name: uipath-automation-discovery description: "UiPath automation discovery — mines Slack/email/wikis/CRM/HRIS/ERP for repetitive work, SPOFs, and replicable models; produces a 4-tier prioritized opportunity report with UiPath implementation paths. Use to discover automation opportunities, find what to automate, or run an internal automation audit across an organization. For building a specific automation→uipath-rpa, authoring a Flow→uipath-maestro-flow, working with agents→uipath-agents." --- # Automation Discovery Investigate how employees actually work, then identify and prioritize internal automation opportunities backed by real behavioral evidence. Produces a UiPath-ready backlog with recommended implementation paths. ## When to Use This Skill - User asks to **discover automation opportunities** across their organization — before any specific automation project exists - User wants to **find manual work to automate** and build a UiPath implementation backlog - User asks "what should we automate?" while working with UiPath tools - User wants an **internal automation audit** to feed into UiPath Automation Hub or a UiPath pipeline - User explicitly invokes `/uipath-automation-discovery` ## Critical Rules 1. **Authorization and privacy first.** Confirm the requester is authorized to analyze the selected systems and employee data. Avoid private channels, DMs, and special-category HR data (payroll, performance reviews) unless explicitly approved. Pseudonymize SPOFs by default (e.g., "Sales Ops Lead A"); use real names only when explicitly authorized. Maintain consistent pseudonyms across the entire report — assign each individual a stable label on first mention and reuse it throughout. Ask about jurisdiction constraints (GDPR, works council, internal policy); apply the stricter rule when uncertain. 2. **Never assume — always ask first.** Complete the full intake (Phase 0) before mining. You need company context, tool access, org structure, privacy scope, and scope agreement. 3. **Verify access before mining.** Test each data source with a minimal read-only operation. If access fails, note it and move on — don't block discovery. 4. **Evidence over opinion.** Every opportunity (Tiers 1-3) must cite a specific source, quantitative metric, and affected role or team. No unsupported claims. If a source yields fewer than 5 signals, mark all findings from that source as low-confidence. Do not promote low-confidence findings above Tier 3, except per Rule 5. 5. **Replication is always Tier 1.** A proven model backed by a working automation that could replicate elsewhere is the highest-value finding — this overrides Rule 4's Tier 3 cap. If the replicable model's source has fewer than 5 signals, classify as Tier 1 with a low-confidence flag until corroborated by a second source. Always lead with replicable models. Never skip the replicable-model search (Phase 2C). ## Workflow Overview ``` Phase 0: INTAKE → Gather context, verify access, agree on scope and privacy Phase 1: MINE → Gather raw data from all verified sources Phase 2: ANALYZE → Extract patterns, SPOFs, replicable models, gaps Phase 3: REFLECT → Layer on business strategy for strategic gaps Phase 4: REPORT → Produce prioritized report with 4 tiers Phase 5: HANDOFF → Map opportunities to UiPath implementation skills ``` **Stop conditions:** Quick scan caps at 10 findings, Standard at 25, Deep dive at 35. Max 2 retries per failed source. Phase 1 timeboxed at 3 hours for deep dives. See [references/intake-guide.md](references/intake-guide.md) §0G for details. ## Phase 0: INTAKE (interactive) Build a complete picture before mining. Ask — don't assume. See [references/intake-guide.md](references/intake-guide.md) for detailed steps covering company context, tool inventory, access verification, org structure, output preferences, user hypotheses, scope control, and privacy authorization. **Key outputs from intake:** - Company context and department list - Tool & system inventory with verified access - Agreed scope (quick scan / standard / deep dive) with finding caps - Privacy scope (pseudonymize by default, jurisdiction constraints) ## Phase 1: MINE Cast a wide net. Prioritize by signal density. Use parallel agents (Agent tool with `subagent_type: general-purpose`, one agent per source category). See [references/mining-guide.md](references/mining-guide.md) for detailed per-source guidance on what to look for and how to search. **Source priority when time is limited:** 1. Messaging help channels — highest signal, fastest to mine 2. Email patterns — reveals hidden recurring work 3. CRM/ERP — reveals structured process bottlenecks 4. Wiki/docs — reveals existing automation landscape 5. Issue tracker — reveals service desk patterns 6. HRIS — reveals people-process friction 7. Web research — reveals strategic gaps Note: Web research (priority 7) feeds Phase 3 strategic analysis. Even under time pressure, do a brief web search for the company's public financials and strategy — this takes minutes and enables Tier 4 findings. Work with whatever access is verified. Even messaging channels alone can yield 15+ opportunities. Each additional source adds depth, not changes the methodology. **Checkpoint:** After Phase 1, share a raw signal summary with the user: "I found X help channels, Y existing automation projects, Z departments. Want me to go deeper on anything before I analyze?" If the user requests deeper mining, run at most 1 additional targeted pass, then proceed. ## Phase 2: ANALYZE Transform raw data into structured findings. ### 2A. Behavioral Patterns Per department, answer: What's manual? What questions repeat? What approvals stall? What reports are compiled by hand? What data is swivel-chaired between systems? What handoffs break? What scheduled tasks are done by humans? ### 2B. Single Points of Failure Identify roles that are sole responders. If they're out, the process stops. Pseudonymize by default — use role/team labels unless naming is authorized. ``` | Role/Pseudonym | System/Channel | Function | Risk | ``` These are the highest-urgency targets. ### 2C. Proven Replicable Models The most important finding. Look for automation already working in one area that could replicate to others: - Bot in one channel but not others - Auto-routing in one team but manual elsewhere - Dashboard auto-generated for one dept but compiled by hand for another ``` | Working Model | Where It's Missing | Addressable Volume | ``` **Greenfield case:** If no existing automations are found (nothing to replicate), Tier 1 will be empty. Promote the highest-volume Tier 2 finding to the headline slot and note that the company has no proven models to replicate yet. ### 2D. Department Coverage Map ``` | Department | Existing Automations | Key Gap | ``` Flag ZERO-coverage departments as biggest blind spots. ### 2E. Process Deep Reads For promising existing projects, extract: pain point, manual process today, volume/frequency, ROI if documented, systems involved, dev status. Apply low-confidence handling per Critical Rule 4. **Checkpoint:** Share analysis summary with user before reflecting: "Here are the top patterns, SPOFs, and replicable models. Anything surprise you? Anything I should investigate further?" If the user requests deeper analysis, run at most 1 additional targeted pass, then proceed to Phase 3. ## Phase 3: REFLECT Identify gaps behavioral data won't reveal. ### 3A. Business Context Research via web search, investor docs, or internal strategy pages: revenue, growth, strategic priorities, competitive challenges, key metrics. ### 3B. Strategic Gaps For each of the company's documented strategic priorities, ask: "Is there an internal automation that accelerates this?" Only include Tier 4 opportunities that map to both a documented strategic priority and an observed Phase 1-2 gap. Use this table as a starting prompt (covers common enterprise priorities) — adapt to the company's actual strategy and do not include rows where no gap was observed: | Priority | Potential Automation | |---|---| | Revenue growth | Lead scoring, pipeline acceleration, renewal prediction | | Cost reduction | Self-service portals, report automation, process standardization | | Customer retention | Health scoring, churn prediction, proactive outreach | | Market expansion | Localization, compliance automation, partner enablement | | Compliance | Audit trails, policy enforcement, automated reporting | | Talent retention | Onboarding, engagement monitoring, career pathing | ### 3C. Dogfooding Check (skip unless the company sells automation/AI/productivity tools) Does the company use its own product internally? Is there a coverage metric? What's the narrative gap between what they sell and what they do internally? ## Phase 4: REPORT Produce a prioritized report in the user's preferred platform. See [references/report-template.md](references/report-template.md) for structure, tier definitions, evidence standards, and platform-specific guidance. ### Quality Bar - Every opportunity has specific evidence (source, metric, affected role/team) - No unsupported claims (except Tier 4, which references strategy docs) - SPOFs identified by role (or name if authorized) - Replicable models highlighted as Tier 1 - Department map is complete (all departments, not just gapped ones) - ROI benchmarks from existing projects included - Strategic analysis ties to real financials ## Phase 5: HANDOFF Map each Tier 1-2 opportunity to a UiPath implementation path. Add a "Next Step" column to the report's Tier 1-2 tables. | Opportunity Type | Recommended Skill | Artifact | |---|---|---| | Desktop/app automation (UI, data entry) | →uipath-rpa | Coded workflow (.cs) or XAML | | Multi-step automation or orchestration | →uipath-maestro-flow | Flow (.flow) | | Scheduled / triggered automation | →uipath-maestro-flow | Flow with trigger | | Agent-based (conversational, reasoning) | →uipath-agents | Coded agent | | Approval / human review gate | →uipath-human-in-the-loop | HITL node in Flow | | Cross-system integration | →uipath-platform | Integration Service connector | For complex or multi-component opportunities, hand off to →uipath-planner for full solution design. ## Execution Strategy Parallelize Phases 1-3 (Phase 0 is interactive — do not parallelize intake). Max 3 concurrent agents using the Agent tool with `subagent_type: general-purpose`: - Phase 1: 3 agents — messaging, wiki/tracker, systems of record - Phase 2: department-specific behavioral agents (max 3 concurrent) - Multiple process doc reads in parallel - Web research concurrent with internal mining Always share interim findings. Don't disappear for hours. Check in after each phase with a brief summary and ask if the user wants to adjust scope. ## Reference Navigation - [references/intake-guide.md](references/intake-guide.md) — Phase 0 detailed steps (company context, tool inventory, access verification, privacy) - [references/mining-guide.md](references/mining-guide.md) — Per-source search guidance (load during Phase 1) - [references/report-template.md](references/report-template.md) — Output structure, tier definitions, and evidence standards (load during Phase 4) ## Anti-patterns - **Mining before intake.** Never start searching systems before completing Phase 0. Without context you'll waste time on irrelevant signals. - **Naming individuals without consent.** Always pseudonymize SPOFs unless the requester explicitly authorizes naming. - **Fabricating metrics.** If a source returns sparse data, mark findings as low-confidence. Never invent volume numbers. - **Promising ROI without source citations.** Every ROI estimate must reference an existing project benchmark or explicit data point. - **Skipping the replicable-model search.** The highest-value findings are always proven models that can replicate. Never skip Phase 2C. - **Speculating from insufficient evidence.** Below signal threshold → mark low confidence. Insufficient evidence → don't promote to Tier 1-3.