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Krishna Anbalagan"},"license":"MIT","homepage":"https://footprintjs.github.io/footPrint/","keywords":["explainability","xai","ai-agent","mcp","decision-engine","rule-engine","audit-trail","causal-trace","flowchart","pipeline","workflow","llm","openapi","narrative","observability","tracing","state-management","time-travel-debugging","typescript","footprint"],"repository":{"url":"git+https://github.com/footprintjs/footPrint.git","type":"git"},"description":"Explainable backend flows — automatic causal traces, decision evidence, and MCP tool generation for AI agents","maintainers":[{"name":"sanjay1909","email":"sanjay1909@gmail.com"}],"readme":"<p align=\"center\">\n  <h1 align=\"center\">FootPrint</h1>\n  <p align=\"center\">\n    <strong>The flowchart pattern for backend code &mdash; self-explainable systems that AI can reason about.</strong>\n  </p>\n</p>\n\n<p align=\"center\"><sub>Part of the <a href=\"https://footprintjs.github.io/\"><b>footprintjs ecosystem</b></a> &mdash; the self-explaining stack.</sub></p>\n\n<p align=\"center\">\n  <a href=\"https://github.com/footprintjs/footPrint/actions\"><img src=\"https://github.com/footprintjs/footPrint/actions/workflows/ci.yml/badge.svg\" alt=\"CI\"></a>\n  <!-- coverage-badge --><img src=\"https://img.shields.io/badge/coverage-93%25-brightgreen.svg\" alt=\"coverage: 93%\"><!-- /coverage-badge -->\n  <a href=\"https://www.npmjs.com/package/footprintjs\"><img src=\"https://img.shields.io/npm/v/footprintjs.svg?style=flat\" alt=\"npm version\"></a>\n  <a href=\"https://bundlephobia.com/package/footprintjs\"><img src=\"https://img.shields.io/bundlephobia/minzip/footprintjs?label=minzipped\" alt=\"minzipped size\"></a>\n  <a href=\"#tree-shakeable--esm-first\"><img src=\"https://img.shields.io/badge/tree--shakeable-%E2%9C%93-success?style=flat\" alt=\"tree-shakeable\"></a>\n  <a href=\"https://github.com/footprintjs/footPrint/blob/main/LICENSE\"><img src=\"https://img.shields.io/badge/license-MIT-blue.svg\" alt=\"MIT License\"></a>\n  <a href=\"https://www.npmjs.com/package/footprintjs\"><img src=\"https://img.shields.io/npm/dm/footprintjs.svg\" alt=\"Downloads\"></a>\n  <a href=\"https://footprintjs.github.io/footprint-playground/samples/llm-agent-tool\"><img src=\"https://img.shields.io/badge/Try_with_LLM-Live_Demo-7c6cf0?style=flat\" alt=\"Try with LLM\"></a>\n  <a href=\"https://footprintjs.github.io/footprint-playground/\"><img src=\"https://img.shields.io/badge/Playground-37%2B_samples-6366f1?style=flat\" alt=\"Interactive Playground\"></a>\n  <a href=\"https://footprintjs.github.io/footPrint/\"><img src=\"https://img.shields.io/badge/Docs-footprintjs-3178c6?style=flat&logo=typescript&logoColor=white\" alt=\"Docs\"></a>\n</p>\n\n<br>\n\n<p align=\"center\">\n  <img src=\"assets/hero.gif\" alt=\"FootPrint demo — loan application with animated flowchart, memory inspector, and causal trace\" width=\"800\">\n</p>\n\n**MVC is a pattern for backends. FootPrint is a different pattern** &mdash; the flowchart pattern &mdash; where your business logic is a graph of functions with transactional state. The code becomes self-explainable: AI reads the structure, traces every decision, and explains what happened &mdash; no hallucination.\n\n```bash\nnpm install footprintjs\n```\n\n---\n\n## The Problem\n\nYour LLM needs to explain why your code made a decision. Without structure, it reconstructs reasoning from scattered logs &mdash; expensive, slow, and hallucinates.\n\n| | MVC / Traditional | Flowchart Pattern (FootPrint) |\n|---|---|---|\n| **LLM explains a decision** | Reconstruct from scattered logs | Read the causal trace directly |\n| **Tool descriptions for agents** | Write and maintain by hand | Auto-generated from the graph |\n| **State management** | Global/manual, race-prone | Transactional scope with per-stage staged commits |\n| **Debugging** | `console.log` + guesswork | Time-travel replay to any stage |\n\n---\n\n## How It Works\n\nA loan pipeline rejects Bob. The user asks: **\"Why was I rejected?\"**\n\nThe runtime auto-generates this trace from what the code actually did:\n\n```\nStage 1: The process began with ReceiveApplication.\n  Step 1: Write creditScore = 580, dti = 0.6, employmentStatus = \"self-employed\"\nStage 2: Next step: Evaluate risk tier from all flags.\n  Step 1: Read creditScore = 580\n  Step 2: Write riskTier = \"high\"\n  Step 3: Write riskFactors = (3 items)\nStage 3: Next step: Route based on risk tier.\n  Step 1: Read riskTier = \"high\"\n[Condition]: It evaluated \"High risk\": riskTier \"high\" eq \"high\" ✓, and chose RejectApplication.\nStage 4: Next step: Generate rejection.\n  Step 1: Write decision = \"REJECTED — below-average credit; DTI exceeds 43%; Self-employed < 2yr\"\n```\n\nThe LLM backtracks through the trace, reading `&larr;` as *caused-by* &mdash; each value links to the write that produced it: `riskTier=\"high\"` &larr; `riskFactors` &larr; `creditScore=580`, `dti=0.6`. Every variable links to its cause:\n\n> **LLM:** \"Your application was rejected because your debt-to-income ratio of 60% exceeds the 43% maximum, your credit score of 580 falls in the 'fair' tier, and your self-employment tenure of 1 year is below the 2-year minimum.\"\n\nThat answer came from the trace &mdash; not from the LLM's imagination.\n\n---\n\n## Quick Start\n\n```typescript\nimport { flowChart, decide, narrative } from 'footprintjs';\n\n// 1. Define your state\ninterface State {\n  user: { name: string; tier: string };\n  discount: number;\n  lane: string;\n}\n\n// 2. Build the flowchart\nconst chart = flowChart<State>('FetchUser', async (scope) => {\n    scope.user = { name: 'Alice', tier: 'premium' };\n  }, 'fetch-user')\n  .addFunction('ApplyDiscount', async (scope) => {\n    scope.discount = scope.user.tier === 'premium' ? 0.2 : 0.05;\n  }, 'apply-discount')\n  .addDeciderFunction('Route', (scope) => {\n    return decide(scope, [\n      { when: { discount: { gt: 0.1 } }, then: 'vip', label: 'High discount' },\n    ], 'standard');\n  }, 'route', 'Route by discount tier')\n    .addFunctionBranch('vip', 'VIPCheckout', async (scope) => {\n      scope.lane = 'VIP express';\n    })\n    .addFunctionBranch('standard', 'StandardCheckout', async (scope) => {\n      scope.lane = 'Standard';\n    })\n    .setDefault('standard')\n    .end()\n  .build();\n\n// 3. Run — capture the narrative recorder so you can read the trace back\nconst trace = narrative();\nconst result = await chart.recorder(trace).run();\n\nconsole.log(result.state.lane);                          // \"VIP express\"\nconsole.log(trace.getEntries().map((e) => e.text).join('\\n'));\n// Stage 1: The process began with FetchUser.\n//   Step 1: Write user = {name, tier}\n// Stage 2: Next, it moved on to ApplyDiscount.\n//   Step 1: Read user = {name, tier}\n//   Step 2: Write discount = 0.2\n// Stage 3: Next step: Route by discount tier.\n//   Step 1: Read discount = 0.2\n// [Condition]: It evaluated Rule 0 \"High discount\": discount 0.2 gt 0.1 ✓, and chose VIPCheckout.\n// Stage 4: Next, it moved on to VIPCheckout.\n//   Step 1: Write lane = \"VIP express\"\n```\n\n> **[Try it in the browser](https://footprintjs.github.io/footprint-playground/)** &mdash; no install needed\n>\n> **[Browse 37+ examples](https://footprintjs.github.io/footprint-playground/)** &mdash; patterns, recorders, subflows, integrations, and a full loan underwriting demo\n\n---\n\n## Vocabulary\n\nIf you know agent or backend systems, you already know these &mdash; here's footprint's name for each:\n\n| footprint term | = the thing you already know |\n|---|---|\n| **scope** | the run's shared **state** (an agent's working memory) &mdash; but every read/write is tracked |\n| **stage** | a **step** / node in the flowchart |\n| **decider** / **selector** | a **router** (picks one branch) / **parallel fan-out** (picks many) |\n| **subflow** | a nested flowchart you compose like a **function** |\n| **recorder** | an **observer** &mdash; called on each read, write, and decision |\n| **narrative** | the execution **trace** rendered as plain-English sentences (the LLM-readable form) |\n| **commit log** | the ordered record of **what each step wrote** &mdash; powers time-travel replay |\n\n---\n\n## Try With Your LLM\n\nExpose any flowchart as an MCP tool in one line &mdash; the description, input schema, and step list are auto-generated from the graph.\n\n```typescript\nconst tool = chart.toMCPTool();\n// { name: 'AssessCredit', description: 'FlowChart: AssessCredit\\nSteps:\\n1. AssessCredit\\n2. ...', inputSchema: { type: 'object', properties: {} } }\n\n// Register with any MCP server or pass directly to the Anthropic SDK:\nconst anthropicTool = { name: tool.name, description: tool.description, input_schema: tool.inputSchema };\n```\n\nThe LLM calls the tool, gets back the decision and causal trace, and explains the result to the user &mdash; all from the same graph that runs in production.\n\n> **[Live demo: Claude calls a credit-decision flowchart as an MCP tool](https://footprintjs.github.io/footprint-playground/samples/llm-agent-tool)** &mdash; enter your API key, watch the tool call happen, see the trace.\n\n---\n\n## Human-in-the-Loop\n\nA stage can stop in the middle of its body to ask a person, and pick the run back up later &mdash; minutes or days later, in a different process.\n\n```typescript\nimport { flowChart, FlowChartExecutor, interrupt } from 'footprintjs';\n\ninterface RefundState { amount: number; approved: boolean; [key: string]: unknown }\n\nconst refundChart = flowChart<RefundState>('Assess refund', (scope) => {\n  scope.amount = 4200;                              // runs AGAIN on resume — keep it idempotent\n\n  const answer = interrupt<{ approved: boolean }>(scope, {\n    reason: `Approve a $${scope.amount} refund?`,\n    expects: { approved: 'boolean' },               // carried verbatim, so a UI can render the form\n  });\n\n  scope.approved = answer.approved;                 // reached only after resume()\n}, 'assess').build();\n\nconst refundExecutor = new FlowChartExecutor(refundChart);\nawait refundExecutor.run();\n\nif (refundExecutor.isPaused()) {\n  const checkpoint = refundExecutor.getCheckpoint()!;   // plain JSON — persist it anywhere\n  // ...a human answers; then, possibly on another server:\n  await new FlowChartExecutor(refundChart).resume(checkpoint, { approved: true });\n}\n```\n\nResume re-enters the stage **from its top** &mdash; stages are atomic, so everything before the `interrupt()` call runs again and the answer comes back out of that call. When you don't want the first half re-run, `addPausableFunction` is the declared alternative: it splits the stage into an `execute` half and a `resume` half.\n\n---\n\n## Features\n\n| Feature | Description |\n|---------|-------------|\n| **Causal Traces** | Every read/write captured &mdash; LLMs backtrack through variables to find causes |\n| **Decision Evidence** | `decide()` / `select()` auto-capture WHY a branch was chosen &mdash; operators, thresholds, pass/fail |\n| **TypedScope&lt;T&gt;** | Typed property access &mdash; `scope.creditScore = 750` instead of `scope.setValue('creditScore', 750)` |\n| **Auto Narrative** | Build-time descriptions for tool selection, runtime traces for explanation |\n| **7 Patterns** | Linear, parallel fork, conditional, multi-select, subflow, streaming, loops |\n| **Transactional State** | Per-stage staged commits, safe merges, time-travel replay |\n| **PII Redaction** | Per-key or declarative `RedactionPolicy` with audit trail |\n| **Flow Recorders** | 7 loop-compression strategies (+ a subflow Manifest recorder) |\n| **Combined Recorders** | Single-hook observers that span data-flow + control-flow &mdash; `executor.attachCombinedRecorder(r)` |\n| **Deferred observers** *(new in 9.6)* | `attach*Recorder(rec, { delivery: 'deferred' })` &mdash; observers run \"one beat behind\" on a bounded queue instead of inside the engine hot path. Honest backpressure (`drop-oldest`/`sample`/`block`), terminal flush at run resolve/reject/pause, `snapshot.observerStats`. [Guide →](./docs/guides/observers-deferred.md) |\n| **Contracts** | I/O schemas (Zod/JSON Schema) + OpenAPI 3.1 + MCP tool generation |\n| **Cancellation** | AbortSignal, timeout, early termination via `scope.$break(reason?)` with optional reason |\n| **Declarative retry** *(new in 9.15)* | `.retry({ attempts, backoffMs, retryOn })` on a stage &mdash; because a retry hand-rolled inside a stage function is invisible to the trace. Every failed attempt fires `onStageRetry` and appears in the narrative, in order, inside its own stage. A failed attempt's writes are discarded (the next attempt starts from committed state); the final attempt keeps commit-on-error exactly. One `runtimeStageId`, one commit bundle, however many attempts ran. [Guide &rarr;](./docs/guides/error-handling.md#declarative-retry) |\n| **Subflow break propagation** | Mount a subflow with `propagateBreak: true` &mdash; inner `$break` terminates the parent loop, with drill-down preserved |\n| **Emit channel** | `scope.$emit(name, payload)` &mdash; user-authored structured events to `EmitRecorder`, pass-through, zero-allocation when no recorder attached, redactable via `emitPatterns` |\n| **Detach** *(new in 4.17)* | `scope.$detachAndForget(driver, child, input)` and `scope.$detachAndJoinLater(driver, child, input)` &mdash; fire-and-forget child flowcharts via the `footprintjs/detach` subpath. Six built-in drivers (microtask / immediate / setImmediate / setTimeout / sendBeacon / workerThread) + custom-driver protocol. Builder-native composition (`addDetachAndForget` / `addDetachAndJoinLater`) makes detach a labeled chart stage. `flushAllDetached()` for graceful shutdown. [Guide →](https://footprintjs.github.io/footPrint/guides/patterns/detach/) |\n| **Recorder storage primitives** | `BoundaryStateStore<TState>` &mdash; one of three composable storage shelves alongside `SequenceStore<T>` (durable ordered, with `getEntryRanges()`) and `KeyedStore<T>` (durable 1:1). `BoundaryStateStore` tracks live transient state DURING a `[start, stop]` event interval (LLM stream partial, tool args streaming, agent turn state) and clears on stop. O(1) reads via `get` / `hasActive` / `activeCount`. Mental model: recorder *interfaces* (`ScopeRecorder` / `FlowRecorder` / `EmitRecorder`) are observers; stores are *bookkeeping shelves*. A real recorder picks ONE observer interface and OWNS the store as a field (composition &mdash; \"one purpose per recorder\"). The `Store` classes are exported from `footprintjs/trace` and are the only recorder-storage model &mdash; there are no abstract base classes to extend. [Guide →](https://footprintjs.github.io/footPrint/guides/features/recorder-storage-primitives/) |\n\n---\n\n## Tree-shakeable & ESM-first\n\nImport one thing, ship one thing. footprintjs is built so your bundle grows only with what you actually use:\n\n- **Dual build, true ESM.** Ships CommonJS (`require`) **and** real ECMAScript Modules (`import`) with TypeScript types. The ESM build is marked `type:module` and every internal import carries an explicit `.js` extension, so it loads as true ESM under Node, Vite, Next, Deno, and Bun — no compatibility shims.\n- **Per-file modules + `sideEffects:false`.** The dist is emitted file-by-file (never pre-bundled) and declares zero side effects, so bundlers can drop every export you don't touch.\n- **Subpath exports.** Pull execution tracing from `footprintjs/trace`, fire-and-forget children from `footprintjs/detach`, engine internals from `footprintjs/advanced` — each is independently tree-shakeable.\n\n**Proven, not promised.** A CI smoke test bundles a minimal `import { flowChart } from 'footprintjs'` and asserts the recorder, detach, and trace layers are pruned — your flowchart core doesn't drag them in. See [`test/esm-packaging.test.ts`](test/esm-packaging.test.ts).\n\n```ts\n// Only flowChart? The recorder/detach/trace layers are tree-shaken away.\nimport { flowChart } from 'footprintjs';\n```\n\n---\n\n## Dev Mode\n\nfootprintjs ships with developer-only diagnostics that are OFF in production (zero overhead). Turn them on during development to catch mistakes early:\n\n```ts\nimport { enableDevMode } from 'footprintjs';\n\nif (process.env.NODE_ENV !== 'production') {\n  enableDevMode();\n}\n```\n\nOne flag gates every library dev-only check:\n\n| Check | What it warns about |\n|---|---|\n| Circular refs | `scope.setValue(...)` called with an object that references itself |\n| Empty recorders | `attachCombinedRecorder(r)` with `r` that has no `on*` handler (likely mistake) |\n| Suspicious predicates | `decide()` / `select()` rules with shapes that probably won't match |\n| Snapshot integrity | `getSubtreeSnapshot()` asked for a path that doesn't exist |\n\nAll dev warnings are `console.warn`. Use `disableDevMode()` to silence them at runtime.\n\n---\n\n## AI Coding Tool Support\n\nFootPrint ships with built-in instructions for every major AI coding assistant. Your AI tool understands the API, patterns, and anti-patterns out of the box.\n\n```bash\n# Download and run the setup script from GitHub\nnpx degit footprintjs/footPrint/ai-instructions footprint-ai && bash footprint-ai/setup.sh && rm -rf footprint-ai\n```\n\n| Tool | What gets installed |\n|------|-------------------|\n| **Claude Code** | `.claude/skills/footprint/SKILL.md` + `CLAUDE.md` |\n| **OpenAI Codex** | `AGENTS.md` |\n| **GitHub Copilot** | `.github/copilot-instructions.md` |\n| **Cursor** | `.cursor/rules/footprint.md` |\n| **Windsurf** | `.windsurfrules` |\n| **Cline** | `.clinerules` |\n| **Kiro** | `.kiro/rules/footprint.md` |\n\n---\n\n## Roadmap — community extension points\n\nThese are deliberately deferred ideas where footprintjs aims to be a *true\ndeveloper's friend*: ship a great zero-config default, but let teams who need it\n**bring their own** implementation. Contributions welcome — open an issue to\ndiscuss before a PR.\n\n- **Pluggable performance primitives (bring-your-own).** Hot-path internals\n  (`deepEqual` for change-only commits, `deepSmartMerge`, deep clones) are\n  built-in today. A future opt-in would let extreme-throughput consumers inject\n  their own (e.g. a SIMD fast-deep-equal or structural-sharing clone) while\n  everyone else keeps the default. Must honour the existing structural-equality\n  contract (a wrong comparator could drop real changes), so it ships with a\n  documented contract + dev-mode validation. See\n  [Commit change semantics](./docs/design/commit-change-semantics.md).\n\n## FAQ\n\n**Are recorders blocking? Do observers slow my chart down?**\nInline (default) recorders run synchronously inside the producing statement.\nIf an observer is heavy, opt it into the deferred tier:\n`executor.attachScopeRecorder(rec, { delivery: 'deferred' })` — events are\ncaptured into one bounded, totally-ordered queue and delivered at the next\nmicrotask checkpoint (\"one beat behind\"), fully drained before `run()`\nreturns. Same record, same order; the engine stops paying for observation.\nFull model + FAQ: [Deferred observers guide](./docs/guides/observers-deferred.md).\n\nHow it stays fast, as patterns with numbers and the tests that pin them: [Performance patterns](./docs/guides/performance-patterns.md).\n\nThe record is the interface — write its shape from any runtime and get time travel, the fold and the Lens: [The record contract](./docs/guides/record-contract.md).\n\n---\n\n## Documentation\n\n| Resource | Link |\n|----------|------|\n| **Getting Started** | [Quick Start](https://footprintjs.github.io/footPrint/getting-started/quick-start/) &middot; [Key Concepts](https://footprintjs.github.io/footPrint/getting-started/key-concepts/) &middot; [Why footprintjs?](https://footprintjs.github.io/footPrint/getting-started/why/) |\n| **Guides** | [Building](https://footprintjs.github.io/footPrint/guides/building/) &middot; [Decision branching](https://footprintjs.github.io/footPrint/guides/decision-branching/) &middot; [Recorders](https://footprintjs.github.io/footPrint/guides/recording/) &middot; [Subflows](https://footprintjs.github.io/footPrint/guides/subflows/) &middot; [Self-describing APIs](https://footprintjs.github.io/footPrint/guides/self-describing/) &middot; [Execution model & limits](./docs/guides/execution-model.md) |\n| **API Reference** | [flowChart() / Builder](https://footprintjs.github.io/footPrint/api/flowchart/) &middot; [decide() / select()](https://footprintjs.github.io/footPrint/api/decide/) &middot; [FlowChartExecutor](https://footprintjs.github.io/footPrint/api/executor/) &middot; [Recorders](https://footprintjs.github.io/footPrint/api/recorders/) &middot; [Contract & Self-describing](https://footprintjs.github.io/footPrint/api/contract/) |\n| **Try it** | [Interactive Playground](https://footprintjs.github.io/footprint-playground/) &middot; [Try with your LLM](https://footprintjs.github.io/footprint-playground/try-with-ai) &middot; [Live Demo](https://footprintjs.github.io/footprint-demo/) |\n\n---\n\n## The footprintjs ecosystem\n\nThe self-explaining stack — from backend pipelines to AI agents. → **[overview](https://footprintjs.github.io/)**\n\n| Project | Role |\n|---|---|\n| **footprintjs** ← you are here | the flowchart pattern (core engine) |\n| [agentfootprint](https://footprintjs.github.io/agentfootprint/) | build self-explaining AI agents |\n| [Explainable UI](https://footprintjs.github.io/explainable-ui/) | visualize a footprintjs run |\n| [Lens](https://github.com/footprintjs/agentfootprint-lens) | debug an agentfootprint run |\n| [Thinking UI](https://footprintjs.github.io/agentThinkingUI/) | replay an agent run for non-devs |\n\n---\n\n## Citing\n\nfootprintjs is part of a research program on making software systems explain themselves — every run records *why* it did what it did, as a causal trace. Researching agent transparency, observability, or explainable AI? The [ecosystem map](https://footprintjs.github.io/) is a good starting point.\n\nIf you use footprintjs in academic work, please cite it (or use the \"Cite this repository\" button on GitHub):\n\n```bibtex\n@software{anbalagan_footprintjs,\n  author  = {Anbalagan, Sanjay Krishna},\n  title   = {footprintjs: the self-explaining flowchart engine},\n  url     = {https://github.com/footprintjs/footPrint},\n  license = {MIT},\n  year    = {2024}\n}\n```\n\n---\n\n[MIT](./LICENSE) &copy; [Sanjay Krishna Anbalagan](https://github.com/sanjay1909)\n","readmeFilename":"README.md"}