uipath-insights

# UiPath Insights — Job Monitoring Agent Skill Insights provides analytics and monitoring for UiPath automation execution. This skill covers **job monitoring** — querying aggregated job execution data for dashboards, health checks, and failure investigation. All operations go through `uip insights jobs <subcommand> --output json`. --- ## When to Use - Checking overall automation health (how many jobs ran, how many succeeded) - Investigating job failures (which processes fail most, what are the failure reasons) - Monitoring job execution trends over time (completed/uncompleted timelines) - Getting per-process performance breakdowns - Drilling into specific failure details for investigation > **Not in scope:** Starting, stopping, or managing individual jobs (use `uip or jobs` via uipath-platform). Root-cause debugging of a specific job's error (use uipath-troubleshoot). Queue item metrics, robot utilization, or dashboard CRUD (not yet available in CLI). --- ## Login & Tenant Setup **Default to Production. Only switch environment/org/tenant when explicitly stated in the request.** - If the request mentions no environment, use the current session (defaults to prod `cloud.uipath.com`) - If the request explicitly names an environment/org/tenant, check `uip login status` and re-login if needed ```bash # Check current environment, org, and tenant uip login status --output json # Login to a specific environment (production cloud is the default) uip login --authority https://cloud.uipath.com --tenant MyTenant # Switch tenant within the same environment uip login tenant set MyTenant ``` --- ## Critical Rules 1. **A time range is always required.** Every `uip insights jobs` command needs either `--time-range <minutes>` (relative) or both `--started-after <epoch-ms>` and `--started-before <epoch-ms>` (absolute). Without one, the command fails. For absolute ranges, pass literal epoch-millisecond numbers, resolved beforehand (see Workflow: Absolute Time Range). Common values: - `--time-range 60` — last 1 hour - `--time-range 1440` — last 24 hours - `--time-range 10080` — last 7 days - `--time-range 43200` — last 30 days 2. **Always use `--output json`.** All commands return a JSON envelope: `{ Result: "Success", Code: "<code>", Data: { ... } }`. Parse the `Data` field for the actual metrics. 3. **Filter options are repeatable.** `--folder-key`, `--process-name`, and `--machine-name` can be specified multiple times to filter by several values: `--process-name "ProcessA" --process-name "ProcessB"`. 4. **Empty data is normal.** If no jobs ran in the time window, the response will have `Data` with null/zero/empty fields. This is not an error. 5. **Start with summary, then drill down.** For any investigation, start with `summary` to get the big picture, then use specific subcommands to investigate areas of concern. --- ## Command Reference All commands share these filter options: | Option | Description | |--------|-------------| | `--time-range <minutes>` | Relative time range in minutes | | `--started-after <epoch-ms>` | Absolute start time (Unix epoch ms) | | `--started-before <epoch-ms>` | Absolute end time (Unix epoch ms) | | `--folder-key <guid>` | Filter by folder key (repeatable) | | `--process-name <name>` | Filter by process name (repeatable) | | `--machine-name <name>` | Filter by machine name (repeatable) | | `--timezone-offset <minutes>` | Client timezone offset from UTC | ### summary Get job KPIs: total count, successful count, and average processing time. ```bash uip insights jobs summary --time-range 1440 --output json ``` **Key Data fields:** `jobsCount`, `successfulJobsCount`, `averageProcessingTime` **Use when:** User asks "how are my automations doing?" or "what's my job success rate?" ### completed-timeline Get completed jobs over time, grouped by job state (successful, faulted, stopped, etc.). ```bash uip insights jobs completed-timeline --time-range 1440 --output json ``` **Key Data fields:** `jobState`, `jobCountByTime`, `timestamp` **Use when:** User asks "show me job completion trends" or "when do most jobs run?" ### uncompleted-timeline Get running and pending jobs over time. ```bash uip insights jobs uncompleted-timeline --time-range 1440 --output json ``` **Key Data fields:** `jobState`, `jobCountByTime`, `timestamp` **Use when:** User asks "are there stuck jobs?" or "how many jobs are still running?" ### top-failures Get processes ranked by failure count. ```bash uip insights jobs top-failures --time-range 43200 --output json ``` **Key Data fields:** `processName`, `jobCountByTime` **Use when:** User asks "which processes fail the most?" or "what's causing failures?" ### failures-by-reason Get job failures grouped by exception reason, with total job count for context. ```bash uip insights jobs failures-by-reason --time-range 1440 --output json ``` **Key Data fields:** `processExceptionReason`, `processName`, `robotName`, `jobsCount` **Use when:** User asks "why are jobs failing?" or "what are the common error messages?" ### process-details Get per-process job breakdown with counts by state. ```bash uip insights jobs process-details --time-range 1440 --output json ``` **Key Data fields:** `processName`, `jobAggregate` **Use when:** User asks "show me per-process stats" or "which process has the most faulted jobs?" ### failure-details Get detailed failure information for drill-down investigation. ```bash uip insights jobs failure-details --time-range 1440 --output json ``` **Key Data fields:** `processName`, `machineName`, `processExceptionReason`, `startTime`, `endTime` **Use when:** User asks "show me the details of recent failures" or "which machines are failing?" --- ## Workflow: Investigate Job Health Follow this pattern when a user asks about automation health or job failures: ```bash # 1. Check login uip login status --output json # 2. Get the big picture — how many jobs ran? how many succeeded? uip insights jobs summary --time-range 1440 --output json # 3. If success rate is low, find which processes fail most uip insights jobs top-failures --time-range 1440 --output json # 4. Find out WHY they're failing uip insights jobs failures-by-reason --time-range 1440 --output json # 5. Drill into specific failure details uip insights jobs failure-details --time-range 1440 --output json # 6. For time-based trends, check timelines uip insights jobs completed-timeline --time-range 10080 --output json ``` **Present findings clearly:** After gathering data, summarize for the user: - Total jobs vs successful jobs (derive failure rate) - Top failing processes by name - Most common failure reasons - Which machines are affected - Whether failures are trending up or down --- ## Workflow: Filter by Folder or Process When the user asks about a specific folder or process: ```bash # Filter by folder uip insights jobs summary --time-range 1440 --folder-key "abc-123-def" --output json # Filter by process name uip insights jobs top-failures --time-range 43200 --process-name "Invoice_Processing" --output json # Combine filters uip insights jobs failures-by-reason --time-range 1440 \ --folder-key "abc-123-def" \ --process-name "Invoice_Processing" \ --output json ``` To discover available folder keys, use `uip or folders list --output json` (from the uipath-platform skill). --- ## Workflow: Absolute Time Range When the user specifies an exact date range instead of "last N hours", use `--started-after`/`--started-before` (not `--time-range`). **Two steps, two separate command invocations.** Resolve the dates to epoch milliseconds first, read the numbers from the output, then write the literal numbers into the `uip` command. Never embed `$(date ...)` substitutions or shell variables in `uip insights` flag values — if `date` fails silently (macOS and Linux flags differ), the flag becomes garbage and the query runs against the wrong window, and the logged command no longer shows what range was actually queried. ```bash # Step 1 — resolve each boundary to epoch ms at UTC midnight (run this alone, read the output): date -u -d "2026-07-01 00:00:00" +%s000 # Linux → 1782864000000 date -u -d "2026-07-06 00:00:00" +%s000 # Linux → 1783296000000 date -u -j -f "%Y-%m-%d %H:%M:%S" "2026-07-01 00:00:00" +%s000 # macOS → 1782864000000 ``` ```bash # Step 2 — run each subcommand with the literal resolved values: uip insights jobs summary --started-after 1782864000000 --started-before 1783296000000 --output json ``` ```bash uip insights jobs completed-timeline --started-after 1782864000000 --started-before 1783296000000 --output json ``` The end boundary is exclusive: "July 1st to July 5th" inclusive means `--started-after` = July 1 00:00:00 UTC and `--started-before` = July 6 00:00:00 UTC. --- ## Troubleshooting | Error | Cause | Fix | |-------|-------|-----| | `Not logged in` | Auth expired | `uip login` | | `time range is required` | Missing `--time-range` or `--started-after`/`--started-before` | Add `--time-range 1440` (or your preferred window) | | `API request failed: 401` | Token doesn't have Insights access | Re-login; ensure the org has Insights enabled | | `API request failed: 403` | User has no folder permissions | Check folder assignments in Orchestrator Admin | | `API request failed: 500` | Server error (often missing time range on older deployments) | Ensure time range is provided in the request body | | All Data fields are null/zero | No jobs ran in the given time window | Widen the `--time-range` (try 43200 for 30 days) | --- ## What NOT to Do - **Don't call `uip insights jobs` without a time range.** The server returns a 500 with a misleading success-shaped response. Always pass `--time-range` or `--started-after`/`--started-before`. - **Don't embed `$(date ...)` or shell variables in `uip insights` flag values.** Resolve times in a separate command first, then pass literal epoch-millisecond numbers. Literal values make the executed command auditable and immune to platform `date` differences. - **Don't chain, loop, or parameterize `uip insights` subcommands in one invocation.** Run each subcommand as its own command with the subcommand name written literally — no `&&`/`;` chains, no `for` loops, no shell variables holding the subcommand name. One command per invocation keeps each subcommand's exit status and output attributable. - **Don't start, stop, or manage individual jobs.** This skill is for monitoring and analytics only. Use `uip or jobs start/stop` via uipath-platform to manage jobs. - **Don't construct raw API calls to the Insights endpoint.** The CLI handles auth headers (`X-UiPath-Internal-AccountName`, `X-UiPath-Internal-TenantName`), URL construction, and error handling. Hand-rolling `curl` or `fetch` calls will miss these. - **Don't retry on auth errors.** If `uip insights jobs` returns 401 or "Not logged in", the fix is `uip login`, not retrying the same command. - **Don't use this skill for root-cause debugging.** "Why did job X fail with error Y?" is a troubleshooting question — hand off to uipath-troubleshoot. This skill answers "which processes fail the most and what are the common reasons." --- ## References For deeper guidance, read these files only when needed: - [`references/jobs-commands-guide.md`](references/jobs-commands-guide.md) — Full command reference with all options, response shapes, and example outputs - [`references/investigation-playbook-guide.md`](references/investigation-playbook-guide.md) — Step-by-step playbooks for common investigation scenarios