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Get Started Free →Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
.claude/skills/process-builder/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 76% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 113% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 122% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 255% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 172% | 0% |
Create new process definitions for the babysitter event-sourced orchestration framework.
Processes live in: library/
├── methodologies/ # Reusable development approaches (TDD, BDD, Scrum, etc.)
│ └── [name]/
│ ├── README.md # Documentation
│ ├── [name].js # Main process
│ └── examples/ # Sample inputs
│
└── specializations/ # Domain-specific processes
├── [category]/ # Engineering specializations (direct children)
│ └── [process].js
└── domains/
└── [domain]/ # Business, Science, Social Sciences
└── [spec]/
├── README.md
├── references.md
├── processes-backlog.md
└── [process].jsCreate foundational documentation:
bash# Check existing specializations ls library/specializations/ # Check methodologies ls library/methodologies/
Create:
README.md - Overview, roles, goals, use cases, common flowsreferences.md - External references, best practices, links to sourcesCreate processes-backlog.md with identified processes:
markdown# Processes Backlog - [Specialization Name] ## Identified Processes - [ ] **process-name** - Short description of what this process accomplishes - Reference: [Link to methodology or standard] - Inputs: list key inputs - Outputs: list key outputs - [ ] **another-process** - Description ...
Create .js process files following SDK patterns (see below).
Every process file follows this pattern:
javascript/** * @process [category]/[process-name] * @description Clear description of what the process accomplishes end-to-end * @inputs { inputName: type, optionalInput?: type } * @outputs { success: boolean, outputName: type, artifacts: array } * * @graph * domains: [domain:software-engineering] * skillAreas: [skill-area:your-skill-area] * topics: [topic:your-topic] * roles: [role:your-role] * workflows: [workflow:your-workflow] * * @example * const result = await orchestrate('[category]/[process-name]', { * inputName: 'value', * optionalInput: 'optional-value' * }); * * @references * - Book: "Relevant Book Title" by Author * - Article: [Title](https://link) * - Standard: ISO/IEEE reference */ import { defineTask } from '@a5c-ai/babysitter-sdk'; /** * [Process Name] Process * * Methodology: Brief description of the approach * * Phases: * 1. Phase Name - What happens * 2. Phase Name - What happens * ... * * Benefits: * - Benefit 1 * - Benefit 2 * * @param {Object} inputs - Process inputs * @param {string} inputs.inputName - Description of input * @param {Object} ctx - Process context (see SDK) * @returns {Promise<Object>} Process result */ export async function process(inputs, ctx) { const { inputName, optionalInput = 'default-value', // ... destructure with defaults } = inputs; const artifacts = []; // ============================================================================ // PHASE 1: [PHASE NAME] // ============================================================================ ctx.log?.('info', 'Starting Phase 1...'); const phase1Result = await ctx.task(someTask, { // task inputs }); artifacts.push(...(phase1Result.artifacts || [])); // Breakpoint for human review (when needed) await ctx.breakpoint({ question: 'Review the results and approve to continue?', title: 'Phase 1 Review', context: { runId: ctx.runId, files: [ { path: 'artifacts/output.md', format: 'markdown', label: 'Output' } ] } }); // ============================================================================ // PHASE 2: [PHASE NAME] - Parallel Execution Example // ============================================================================ const [result1, result2, result3] = await ctx.parallel.all([ () => ctx.task(task1, { /* args */ }), () => ctx.task(task2, { /* args */ }), () => ctx.task(task3, { /* args */ }) ]); // ============================================================================ // PHASE 3: [ITERATION EXAMPLE] // ============================================================================ let iteration = 0; let targetMet = false; while (!targetMet && iteration < maxIterations) { iteration++; const iterResult = await ctx.task(iterativeTask, { iteration, previousResults: /* ... */ }); targetMet = iterResult.meetsTarget; if (!targetMet && iteration % 3 === 0) { // Periodic checkpoint await ctx.breakpoint({ question: `Iteration ${iteration}: Target not met. Continue?`, title: 'Progress Checkpoint', context: { /* ... */ } }); } } // ============================================================================ // COMPLETION // ============================================================================ return { success: targetMet, iterations: iteration, artifacts, // ... other outputs matching @outputs }; } // ============================================================================ // TASK DEFINITIONS // ============================================================================ /** * Task: [Task Name] * Purpose: What this task accomplishes */ const someTask = defineTask({ name: 'task-name', description: 'What this task does', // Task definition - executed externally by orchestrator // This returns a TaskDef that describes HOW to run the task inputs: { inputName: { type: 'string', required: true }, optionalInput: { type: 'number', default: 10 } }, outputs: { result: { type: 'object' }, artifacts: { type: 'array' } }, async run(inputs, taskCtx) { const effectId = taskCtx.effectId; return { kind: 'node', // or 'agent', 'skill', 'shell', 'breakpoint' title: `Task: ${inputs.inputName}`, node: { entry: 'scripts/task-runner.js', args: ['--input', inputs.inputName, '--effect-id', effectId] }, io: { inputJsonPath: `tasks/${effectId}/input.json`, outputJsonPath: `tasks/${effectId}/result.json` }, labels: ['category', 'subcategory'] }; } });
The ctx object provides these intrinsics:
| Method | Purpose | Behavior | |--------|---------|----------| | ctx.task(taskDef, args, opts?) | Execute a task | Returns result or throws typed exception | | ctx.breakpoint(payload) | Human approval gate | Pauses until approved via human | | ctx.sleepUntil(isoOrEpochMs) | Time-based gate | Pauses until specified time | | ctx.parallel.all([...thunks]) | Parallel execution | Runs independent tasks concurrently | | ctx.parallel.map(items, fn) | Parallel map | Maps items through task function | | ctx.now() | Deterministic time | Returns current Date (or provided time) | | ctx.log?.(level, msg, data?) | Logging | Optional logging helper | | ctx.runId | Run identifier | Current run's unique ID |
| Kind | Use Case | Executor | |------|----------|----------| | node | Scripts, builds, tests | Node.js process | | agent | LLM-powered analysis, generation | Claude Code agent | | skill | Claude Code skills | Skill invocation | | shell | System commands | Shell execution | | breakpoint | Human approval | Breakpoints UI/service | | sleep | Time gates | Orchestrator scheduling | | orchestrator_task | Internal orchestrator work | Self-routed |
javascriptawait ctx.breakpoint({ question: 'Approve to continue?', title: 'Checkpoint', context: { runId: ctx.runId } });
javascriptawait ctx.breakpoint({ question: 'Review the generated specification. Does it meet requirements?', title: 'Specification Review', context: { runId: ctx.runId, files: [ { path: 'artifacts/spec.md', format: 'markdown', label: 'Specification' }, { path: 'artifacts/spec.json', format: 'json', label: 'JSON Schema' }, { path: 'src/implementation.ts', format: 'code', language: 'typescript', label: 'Implementation' } ] } });
javascriptif (qualityScore < targetScore) { await ctx.breakpoint({ question: `Quality score ${qualityScore} is below target ${targetScore}. Continue iterating or accept current result?`, title: 'Quality Gate', context: { runId: ctx.runId, data: { qualityScore, targetScore, iteration } } }); }
javascriptlet quality = 0; let iteration = 0; const targetQuality = inputs.targetQuality || 85; const maxIterations = inputs.maxIterations || 10; while (quality < targetQuality && iteration < maxIterations) { iteration++; ctx.log?.('info', `Iteration ${iteration}/${maxIterations}`); // Execute improvement tasks const improvement = await ctx.task(improveTask, { iteration }); // Score quality (parallel checks) const [coverage, lint, security, tests] = await ctx.parallel.all([ () => ctx.task(coverageTask, {}), () => ctx.task(lintTask, {}), () => ctx.task(securityTask, {}), () => ctx.task(runTestsTask, {}) ]); // Agent scores overall quality const score = await ctx.task(agentScoringTask, { coverage, lint, security, tests, iteration }); quality = score.overall; ctx.log?.('info', `Quality: ${quality}/${targetQuality}`); if (quality >= targetQuality) { ctx.log?.('info', 'Quality target achieved!'); break; } } return { success: quality >= targetQuality, quality, iterations: iteration };
javascript// Phase 1: Research const research = await ctx.task(researchTask, { topic: inputs.topic }); await ctx.breakpoint({ question: 'Review research findings before proceeding to planning.', title: 'Research Review', context: { runId: ctx.runId } }); // Phase 2: Planning const plan = await ctx.task(planningTask, { research }); await ctx.breakpoint({ question: 'Review plan before implementation.', title: 'Plan Review', context: { runId: ctx.runId } }); // Phase 3: Implementation const implementation = await ctx.task(implementTask, { plan }); // Phase 4: Verification const verification = await ctx.task(verifyTask, { implementation, plan }); await ctx.breakpoint({ question: 'Final review before completion.', title: 'Final Approval', context: { runId: ctx.runId } }); return { success: verification.passed, plan, implementation };
javascript// Fan out to multiple parallel analyses const analyses = await ctx.parallel.map(components, component => ctx.task(analyzeTask, { component }, { label: `analyze:${component.name}` }) ); // Aggregate results const aggregated = await ctx.task(aggregateTask, { analyses }); return { analyses, summary: aggregated.summary };
bash# Create a new run babysitter run:create \ --process-id methodologies/my-process \ --entry ./library/methodologies/my-process.js#process \ --inputs ./test-inputs.json \ --json # Iterate the run babysitter run:iterate .a5c/runs/<runId> --json # List pending tasks babysitter task:list .a5c/runs/<runId> --pending --json # Post a task result babysitter task:post .a5c/runs/<runId> <effectId> \ --status ok \ --value ./result.json # Check run status babysitter run:status .a5c/runs/<runId> # View events babysitter run:events .a5c/runs/<runId> --limit 20 --reverse
json{ "feature": "User authentication with JWT", "acceptanceCriteria": [ "Users can register with email and password", "Users can login and receive a JWT token", "Invalid credentials are rejected" ], "testFramework": "jest", "targetQuality": 85, "maxIterations": 5 }
Ask the user:
| Question | Purpose | |----------|---------| | Domain/Category | Determines directory location | | Process Name | kebab-case identifier | | Goal | What should the process accomplish? | | Inputs | What data does the process need? | | Outputs | What artifacts/results does it produce? | | Phases | What are the major steps? | | Quality Gates | Where should humans review? | | Iteration Strategy | Fixed phases vs. convergence loop? |
bash# Find similar processes ls library/methodologies/ ls library/specializations/ # Read similar process for patterns cat library/methodologies/atdd-tdd/atdd-tdd.js | head -200 # Check methodology README structure cat library/methodologies/atdd-tdd/README.md
bashcat library/methodologies/backlog.md
For Methodologies:
methodologies/[name]/README.md (comprehensive documentation)methodologies/[name]/[name].js (process implementation)methodologies/[name]/examples/ (sample inputs)For Specializations:
specializations/domains/[domain]/[spec]/specializations/[category]/[process].jsChecklist:
@graph block with relevant atlas node IDs (at minimum one domain)@a5c-ai/babysitter-sdkexport async function process(inputs, ctx)// === PHASE N: NAME ===)ctx.log?.('info', message)ctx.task(taskDef, inputs)javascript/** * @process methodologies/my-methodology * @description My development methodology with quality convergence * @inputs { feature: string, targetQuality?: number } * @outputs { success: boolean, quality: number, artifacts: array } */ export async function process(inputs, ctx) { const { feature, targetQuality = 85 } = inputs; // ... implementation }
javascript/** * @process specializations/game-development/core-mechanics-prototyping * @description Prototype and validate core gameplay mechanics through iteration * @inputs { prototypeName: string, mechanicsToTest: array, engine?: string } * @outputs { success: boolean, mechanicsValidated: array, playtestResults: object } */ export async function process(inputs, ctx) { const { prototypeName, mechanicsToTest, engine = 'Unity' } = inputs; // ... implementation }
javascript/** * @process specializations/domains/science/bioinformatics/sequence-analysis * @description Analyze genomic sequences using standard bioinformatics workflows * @inputs { sequences: array, analysisType: string, referenceGenome?: string } * @outputs { success: boolean, alignments: array, variants: array, report: object } */ export async function process(inputs, ctx) { const { sequences, analysisType, referenceGenome = 'GRCh38' } = inputs; // ... implementation }
Every generated process file MUST include a @graph JSDoc block in its file header comment alongside the standard @process, @description, @inputs, and @outputs tags.
javascript/** * @process specializations/my-domain/my-process * @description ... * @inputs { ... } * @outputs { ... } * * @graph * domains: [domain:software-engineering, domain:devops] * skillAreas: [skill-area:caching-strategies] * topics: [topic:microservices, topic:event-sourcing] * roles: [role:backend-engineer, role:sre] * workflows: [workflow:code-review] */
Read the atlas graph domain directory (packages/atlas/graph/domain/) to find valid node IDs. The directory contains YAML files grouped by category:
domains/ — high-level domain nodes (e.g. domain:software-engineering, domain:devops, domain:data-engineering)skill-areas/ — specific skill area nodestopics/ — granular topic nodesroles/ — role nodes (engineers, practitioners, researchers)workflows/ — workflow nodesPick 2–4 edges that genuinely relate to the process. Do not guess IDs — read the actual YAML files to find valid ones. At minimum, every process must reference at least one domain: node.
This metadata connects the process to the atlas knowledge graph. A pre-build generator script parses the @graph block and creates graph nodes and edges for discoverability. Processes without this block will not appear in graph-based search results or recommendations.
library/reference/sdk.mdlibrary/methodologies/backlog.mdlibrary/specializations/backlog.mdlibrary/methodologies/atdd-tdd/library/methodologies/spec-driven-development.jsREADME.md for full framework documentation| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 31,744 | 38,826 | +22% | 1 | 1 | 0% | 6,214 | 10,945 | +76% | 0 | 0 | — |
case-02 | fail→pass | 25,324 | 29,244 | +15% | 1 | 1 | 0% | 5,128 | 10,941 | +113% | 0 | 0 | — |
case-03 | fail→pass | 21,619 | 27,961 | +29% | 1 | 1 | 0% | 4,932 | 10,940 | +122% | 0 | 0 | — |
case-04 | fail→pass | 8,859 | 5,519 | -38% | 1 | 1 | 0% | 1,629 | 5,789 | +255% | 0 | 0 | — |
case-05 | fail→pass | 11,715 | 8,378 | -28% | 1 | 1 | 0% | 2,333 | 6,338 | +172% | 0 | 0 | — |
case-06 | fail→pass | 8,712 | 5,143 | -41% | 1 | 1 | 0% | 1,580 | 5,778 | +266% | 0 | 0 | — |
case-07 | fail→pass | 13,418 | 4,779 | -64% | 1 | 1 | 0% | 2,695 | 5,474 | +103% | 0 | 0 | — |
case-08 | fail→pass | 7,099 | 3,302 | -53% | 1 | 1 | 0% | 1,410 | 5,344 | +279% | 0 | 0 | — |
case-09 | pass→pass | 11,487 | 4,377 | -62% | 1 | 1 | 0% | 2,073 | 5,517 | +166% | 0 | 0 | — |
case-10 | fail→pass | 10,894 | 5,771 | -47% | 1 | 1 | 0% | 2,083 | 5,789 | +178% | 0 | 0 | — |
case-11 | fail→pass | 7,038 | 2,830 | -60% | 1 | 1 | 0% | 1,273 | 5,293 | +316% | 0 | 0 | — |
case-12 | fail→pass | 15,411 | 2,312 | -85% | 1 | 1 | 0% | 3,046 | 5,170 | +70% | 0 | 0 | — |
case-13 | fail→fail | 13,151 | 8,300 | -37% | 1 | 1 | 0% | 2,642 | 6,494 | +146% | 0 | 0 | — |
case-14 | fail→pass | 11,290 | 5,887 | -48% | 1 | 1 | 0% | 2,142 | 5,935 | +177% | 0 | 0 | — |
case-15 | fail→pass | 15,286 | 4,477 | -71% | 1 | 1 | 0% | 2,676 | 5,306 | +98% | 0 | 0 | — |
case-16 | fail→pass | 7,134 | 3,100 | -57% | 1 | 1 | 0% | 1,300 | 5,308 | +308% | 0 | 0 | — |
case-17 | fail→pass | 7,272 | 2,133 | -71% | 1 | 1 | 0% | 1,274 | 5,148 | +304% | 0 | 0 | — |
case-18 | fail→pass | 12,287 | 3,263 | -73% | 1 | 1 | 0% | 2,463 | 5,325 | +116% | 0 | 0 | — |
case-19 | fail→pass | 9,475 | 2,553 | -73% | 1 | 1 | 0% | 1,820 | 5,134 | +182% | 0 | 0 | — |
case-20 | fail→fail | 9,953 | 4,888 | -51% | 1 | 1 | 0% | 2,005 | 5,792 | +189% | 0 | 0 | — |
case-21 | fail→fail | 10,650 | 10,802 | +1% | 1 | 1 | 0% | 2,389 | 6,890 | +188% | 0 | 0 | — |
case-22 | fail→fail | 9,720 | 6,453 | -34% | 1 | 1 | 0% | 1,875 | 6,040 | +222% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +77 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 7/27/2026 | +73% |
Other measured skills in the registry, with their headline benchmark lift.