> ## Documentation Index > Fetch the complete documentation index at: https://docs.mapxagent.com/llms.txt > Use this file to discover all available pages before exploring further. # Workflows and plans > MapX turns a multi-step analysis into a plan you approve, a graph you can watch, and a reusable workflow you can run on new data. MapX has two related ideas for multi-step work: * A **plan** belongs to one project. The AI researches the question, writes a plan document, and waits for your approval before anything runs. * A **workflow** is a published plan turned into a reusable asset: the same steps, with typed input slots instead of hard-coded layers, runnable on other data and shareable with your team. The Workflows catalog, listing published workflows with their inputs and step counts ## Plan first, then run Planning is on by default in the chat input: the AI researches read-only, writes a plan document for you to review, and executes only after you approve. Approval happens on the **decision card** in the chat — the same card that lets you send a revision or abandon the plan, and it stays in the conversation afterwards as a record. The full lifecycle — clarifying questions, the read-only research phase, the seven-chapter document, the decision card and the plan statuses — has its own page: [Plan mode](/en/concepts/plan-mode). Each executed step is a tool run from the [analysis](/en/concepts/analysis) catalog, so results are real layers, tables and charts. A plan is tied to the project it was written for, and it is not re-runnable as-is: to repeat the work on other data, fork it into a new plan or publish it as a workflow. ## Publish a workflow Publishing turns an approved plan into a reusable asset: * **Input slots** replace the layers the plan was written against. The workflow declares what it needs — for example a point layer of candidates and a polygon layer of zones. * **Steps** stay fixed, so the method is reproducible; only the data changes. * **Team sharing** is optional: share the workflow so team members can run it, while only you can edit it. ## Run a published workflow Top menu → **Workflows** lists your saved workflows with their tags, input slots, and step counts. The dashboard has the same library outside a project. For each input slot, pick a layer from the current project. Slots are typed, so a slot that expects polygons only offers polygon layers. Choose **Run**. The execution opens as a graph of the steps, with a live state and a running counter for each. See [The workflow graph](#the-workflow-graph) below for how to read and steer it. Finished steps publish their layers, tables, and reports into the project, where you can open, style, and share them like any other result. ## The workflow graph A run opens as a directed graph rather than a list: one node per step, and an edge wherever a step consumes another step's output. Edges are labelled with what travels along them, so you can see which steps feed which, and where one result branches into several downstream steps. Solid edges carry data; dashed edges are execution-order dependencies or an input slot waiting for data. Every node shows the step's intent and the operator that runs it — Raster Calculator, Euclidean Distance, Clip, Buffer Analysis, and so on — so the same picture doubles as documentation of the method. The workflow graph for a finished run — 42 of 42 steps done, each node showing its operator, with the plan card alongside Node states are live while the run proceeds, using the legend above the canvas: * **Done** — the step finished and published its output. * **Running** — the step the engine is working on right now; edges out of it animate as results land. * **Pending** — not reached yet. Steps that were deliberately skipped are marked **Skipped**. * **Failed** — the step stopped with an error. The counter above the canvas reads *42/42 steps done*, and appends *n failed* if any step failed. ### Reading and steering a run * **Click a node** to open the inspector: intent, operator, parameters, inputs, and artifacts, plus status, duration, credits, and iteration count — or the error and a **Retry step** button when it failed. * **Human gate nodes** wait for you. The inspector shows the question, an answer box, and **Cancel run**. * **A node with no data bound yet** shows **Awaiting data** and offers a shortcut to pick a layer from the current project or from the built-in catalog. * **Pan and zoom** — drag to pan, scroll to zoom, Shift+drag to box-select several nodes; **Esc** returns you to the map. * Switch between **Plan document** and **Workflow** to read the plan text you approved and the graph of the same steps. ## Where runs live | Where | What you see | | - | - | | Right rail → **Plans** | Plans for the current project and the recent runs of each | | Top menu → **Workflows** | Saved workflows, ready to run on new data | | Dashboard → **Workflows** | The team library, including shared workflows | The Plans panel: each plan shows its status, step and input counts, deliverables, and recent runs ## When a step fails A workflow run reports the failing step and offers to **retry that step**; steps that already succeeded are not recomputed. Opening the step's run detail shows the same reason and next step the analysis ledger shows — for example an input budget that was exceeded, a missing field, or data the tool cannot use. Some workflows pause on a **human confirmation** step: the run waits for your answer before continuing. This is how a workflow keeps a judgement call — accepting an unbound input, approving a threshold — visible instead of burying it in code. Deterministic steps (the analysis tools) do not consume AI credits; AI decision steps and the planning conversation do. See [Credits](/en/account/credits). ## Related * [AI chat](/en/concepts/ai-chat) — how plan mode fits into a conversation * [Analysis](/en/concepts/analysis) — the tools a plan is built from * [Scenarios](/en/concepts/scenarios) — start from a prepared study area instead of a blank project * [Reports](/en/concepts/reports) — package a finished run as a deliverable This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.