Orchestrate full-cycle implementation across backend and frontend layers
npx skills add https://github.com/shinpr/claude-code-workflows --skill recipe-fullstack-implement
Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Execute Skill: subagents-orchestration-guide before making workflow decisions, invoking agents, or resolving findings.
Context: Full-cycle fullstack implementation management (Requirements Analysis → Design (backend + frontend) → Planning → Implementation → Quality Assurance)
Core Identity: "I am an orchestrator." (see subagents-orchestration-guide skill)
Local authority gate: Make this recipe's workflow decisions and validate each returned result directly; delegate semantic deliverable production to the named specialist.
Review Resolution Gate [MANDATORY]: Resolve every actionable deliverable-review finding through subagents-orchestration-guide Review Resolution before correction or progression; include declined IDs with governing reasons and evidence in the final user report.
Before the first finding disposition, read references/review-resolution.md from the loaded subagents-orchestration-guide skill.
MANDATORY: Read references/monorepo-flow.md from subagents-orchestration-guide skill BEFORE proceeding. Follow the Fullstack Flow defined there instead of the standard single-layer flow.
CRITICAL: Execute all steps, sub-agents, and stopping points defined in both the monorepo-flow.md reference and subagents-orchestration-guide skill.
Instruction Content: $ARGUMENTS
Assess the current situation:
| Situation Pattern | Decision Criteria | Next Action |
|------------------|------------------|-------------|
| New Requirements | No existing work, new feature/fix request | Start with requirement-analyzer |
| Flow Continuation | Existing docs/tasks present, continuation directive | Identify next step in monorepo-flow.md |
| Quality Errors | Error detection, test failures, build errors | Execute quality-fixer (layer-appropriate) |
| Ambiguous | Intent unclear, multiple interpretations possible | Confirm with user |
When continuing existing flow, verify:
Execute Skill: external-resource-context before running the external resource hearing in monorepo-flow.md.
Follow monorepo-flow.md for the complete design-through-planning flow (Steps 1-17 for Large scale, Steps 1-15 for Medium scale). The flow table in that reference defines every step, agent invocation, parallelization rule, and stop point.
Key points to enforce as the orchestrator runs the flow:
doc_type: WorkPlan) and request batch approval only after the review passesAfter scale determination, use TaskCreate to register each design/planning step and the implementation, verification, cleanup, and report phases. Complete registration before invoking subagents; mark and advance the active phase with TaskUpdate.
Execute Skill: requirement-convergence before running the hearing protocol.
Run the requirement-convergence hearing protocol on the returned convergence object before presenting anything else, using the analyzer's scope facts and cost band as the facts it presents.
When user responds to questions:
convergence field is below ready → Re-execute requirement-analyzer with the hearing answers so the record is re-judged. Repeat until every field is ready or weak-but-explicitscopeDependencies.question → Check impact for scale changeconfidence: "confirmed" or no scale change → Proceed to next stepPre-execution Checklist (MANDATORY):
Required Flow Compliance:
Append the following block to every subagent prompt invoked from this recipe:
Scope boundary for subagents:
Operate within the task scope and referenced files in the prompt.
Use loaded skills to execute that scope.
Escalate when the required fix or investigation falls outside that scope.
Agent routing by task filename (see monorepo-flow.md reference):
*-backend-task-* → dev-workflows:task-executor + dev-workflows:quality-fixer
*-frontend-task-* → dev-workflows-frontend:task-executor-frontend + dev-workflows-frontend:quality-fixer-frontend
Rules:
requiresTestReview is true, invoke integration-test-reviewer with diffBase, changed integration/E2E paths, taskFile, prompt claims, and mutationEvidence, then branch on its status:approved → Continue to rule 3blocked → Escalate to userneeds_revision → Apply the Review Resolution Gateapply findings → Return them to the layer executor, then re-review with prior_feedbackdecline → Continue to rule 3user_decision_required finding → Escalate to usertask_file, upstream mutationEvidence, and qualityCommand when available (caller first, otherwise current task)stub_detected → Return to executor with incompleteImplementations[] detailsblocked → Escalate to userapproved → Proceed to commitResolve all readable Design Docs from the Work Plan, or the Work Plan itself when none exist; missing input blocks verification.
Emit one code-verifier call per resolved document plus one security-reviewer call in one assistant message, then await all:
doc_type, single document_path, and code_paths from git diff --name-only main...HEADgoverningDocuments list and implementationFilesApply subagents-orchestration-guide's Post-Implementation Verification pass/fail and fix/re-run rules with the layer-appropriate executor and quality-fixer. Present the unified report; proceed to Final Cleanup after all pass.
Before the completion report, delete the implementation task files this recipe consumed. Their work is committed; docs/plans/ is ephemeral working state and is not retained between recipe runs:
docs/plans/tasks/{plan-name}-backend-task-*.md and docs/plans/tasks/{plan-name}-frontend-task-*.md (the {plan-name} derived from the work plan path used in this run)docs/plans/tasks/{plan-name}-phase*-completion.md (the per-phase completion files generated by task-decomposer)docs/plans/tasks/_overview-{plan-name}.md if presentdocs/plans/{plan-name}.md) — the user decides whether to delete it after final reviewIf task files cannot be deleted (filesystem error), report the failure but do not block the completion report.
After acceptance-test-generator execution, when invoking work-planner (subagent_type: "dev-workflows:work-planner"), communicate:
generatedFiles.integration)generatedFiles.fixtureE2e)generatedFiles.serviceE2e)e2eAbsenceReason.fixtureE2e and e2eAbsenceReason.serviceE2e, when each lane is null)Deliverable production is executed through the specialist selected by monorepo-flow.md and subagents-orchestration-guide; workflow decisions and returned-result validation remain with the orchestrator.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take shinpr/claude-code-workflows-recipe-fullstack-implement from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.