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recipe-design

Execute from codebase-scoped analysis through optional ADR decisions to complete Design Doc approval

Install / Use

npx skills add shinpr/claude-code-workflows --skill recipe-design

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Supported Platforms

Universal

Our assessment of recipe-design

recipe-design scores 86/100 on our quality scale, 541st of 968 AI & Machine Learning skills we index.

Its SKILL.md is 9.2 KB long, well organised into 10 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

It has 687 GitHub stars, a meaningful sign that others use it.

Substance
29/30
Structure
18/20
Description
12/15
Adoption
12/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so recipe-design is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

recipe-design compared with similar skills

All 4 of these similar skills score higher than recipe-design; compare them before choosing.

SkillScoreStarsUpdatedFormat
recipe-design (this skill)by shinpr866875d agoSKILL.md
claude-memby thedotmack10097.1ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10085.4k1d agoCLAUDE.md
headroomby headroomlabs-ai10074.5ktodayCLAUDE.md
CowAgentby zhayujie10047.3k1d agoCLAUDE.md

Frequently asked questions

How do I install recipe-design?
Run npx skills add shinpr/claude-code-workflows --skill recipe-design. The install tabs above show the steps for each supported agent.
Which AI agents does recipe-design work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is recipe-design safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is recipe-design still maintained?
The repository was last updated 5 days ago, so recipe-design is actively maintained.

name: recipe-design description: Execute from codebase-scoped analysis through optional ADR decisions to complete Design Doc approval disable-model-invocation: true

Explicit User Instruction: The user explicitly instructs and authorizes every subagent call named in this recipe. Execute each applicable call when its prerequisites are met.

Execute Skill: documentation-criteria before document routing or creation. Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts. Execute Skill: subagents-orchestration-guide before invoking agents or resolving findings. Before the first finding disposition, read references/review-resolution.md from the loaded subagents-orchestration-guide skill.

Outcome and Ownership

Coordinate the design phase from repository evidence to an approved Design Doc. The user owns product requirements and exclusions; the orchestrator owns convergence readiness, Structural Scale, ADR qualification, evidence selection, and Review Resolution. Named specialists own semantic investigation and artifact authorship.

The Design Doc is always the complete implementation design for Medium/Large work. A qualifying ADR batch narrows technical choices before the Design Doc, which retains the complete flow and implementation boundary.

Requirements: $ARGUMENTS

Flow

requirement source -> codebase-analyzer -> scope/decision confirmation [Stop]
                                             |
                               optional ADR batch -> batch review [Stop]
                                             |
                 Design Doc -> code-verifier -> Review Resolution
                                             |
                     document-reviewer -> design-sync -> approval [Stop]

Execute each dependent step after its prerequisite evidence exists. Use Review Resolution for every actionable verifier, reviewer, or design-sync finding. Wait at each [Stop] for explicit user confirmation.

At each Invoke below, build the Agent prompt as a mechanical extraction: copy the named source values into the exact fields, apply only the declared serialization, then invoke immediately.

Step 1: Select the Governing Requirement Source

Use the approved PRD path when one exists. Otherwise use the confirmed requirements verbatim.

Set confirmed_requirement_context to the approved PRD path exactly. Only when no approved PRD exists, use the orchestrator-confirmed convergence record unchanged.

Step 2: Collect Decision Material

Invoke dev-workflows:codebase-analyzer:

prd_path: [approved PRD path]

or, when no approved PRD exists:

requirements: [confirmed requirements verbatim]

Invoke once for the complete confirmed scope. Require one valid JSON result and let the analyzer discover affected paths, responsibility boundaries, and cross-layer contracts. Treat its focus areas as existing-behavior safeguards, not as new requirements.

This independent discovery keeps scope and option convergence grounded in repository evidence rather than the orchestrator's unverified implementation hypothesis.

Step 3: Confirm Scope and ADR Decisions

Execute Skill: requirement-convergence. The orchestrator builds and judges the convergence record from the user request and Step 2 evidence.

Judge all four convergence fields. Assign cost from Step 2 structural evidence and record its unknowns; run the hearing only for fields below ready.

Determine Structural Scale from outcomes and responsibility boundaries. File count is supporting evidence only.

Resolve decisionMaterials.candidateDecisionPoints against the governing requirement source, applicable simplifications, reuse, and invalidations. Remove a point when that evidence already converges on one sufficient approach. For each remaining item, apply documentation-criteria filters in order:

  1. Choice requires judgment between at least two credible, materially distinct options inside confirmed scope.
  2. The selection has durable material impact.

Record every passing item as adrDecisionPoints; an empty list routes directly to the Design Doc. ADR creation is limited to items that pass both filters.

Present the requirement-convergence Scope Confirmation. Place target responsibilities with their strongest file evidence, applicable simplifications with their conditions, and each qualifying ADR decision point with its filter evidence or none under Decision evidence; place Structural Scale with its boundary rationale and the recommended document route under Workflow.

Offer proceed, or correct scope and re-run analysis. Ask a question only when its answer can change a convergence field, the confirmed outcome, or scope. Continue only when every convergence field is ready or weak-but-explicit. [Stop: Scope confirmation].

Step 4: Create and Approve an ADR Batch When Needed

When adrDecisionPoints is non-empty:

  1. Invoke dev-workflows:technical-designer once with exact inputs: document_to_create: ADRBatch; confirmed_requirement_context; decision_points as the ordered adrDecisionPoints confirmed in Step 3, unchanged; and decision_materials as the corresponding objects from Step 2 decisionMaterials.candidateDecisionPoints, copied unchanged in that order.
  2. Invoke dev-workflows:document-reviewer once with exact inputs: doc_type: ADRBatch, targets: [all returned paths], and confirmed_requirement_context.
  3. Route the reviewer verdict first: pass proceeds with issues: []; needs_revision applies Review Resolution, updates one ADR per path serially, and re-reviews the complete batch; rejected resolves the governing-source conflict before another review.
  4. Present one batch decision only after a pass review. [Stop: ADR batch approval].
  5. After user approval, update each ADR status to Accepted and verify the changed status.

Step 5: Create the Design Doc

Create the complete MVP implementation design from reviewed artifacts and unchanged repository evidence; this keeps the Design Doc traceable to approved sources instead of an orchestrator-authored shadow design.

Invoke dev-workflows:technical-designer with exactly:

  • document_to_create: DesignDoc;
  • confirmed_requirement_context;
  • structural_scale;
  • adr_paths: [accepted paths or []];
  • codebase_analysis: [complete Step 2 JSON unchanged].

The Design Doc owns the full end-to-end design and retains all applicable downstream safeguards in the documentation-criteria template.

Step 6: Verify and Resolve Repository Claims

Keep verifier observations unchanged so corrections remain traceable to observed repository evidence instead of becoming orchestrator-authored design instructions.

Invoke dev-workflows:code-verifier with doc_type: design-doc and the Design Doc path to verify current premises and feasibility while treating planned behavior as intent.

Apply Review Resolution to every discrepancy before document review. Send only apply findings to a fresh technical-designer update invocation with Operation Mode: update, Existing Document: [Design Doc path], and correction_findings: [complete findings unchanged except for their dispositions]. The designer applies its review-triggered bounded self-verification gate when a finding names an unverified decision-changing premise; this fresh designer is the sole correction specialist and selects the evidence route. Rerun code-verifier after a correction with the previous complete result, dispositions, and correction diff or paths as prior_feedback. Build the single verification_evidence object defined by Review Resolution from the latest result and continue at its convergence condition.

Step 7: Review and Approve

Invoke dev-workflows:document-reviewer with exact inputs: doc_type: DesignDoc, target, review_context: creation, the original user requirements verbatim as requirements_verbatim, confirmed_requirement_context, codebase_analysis, and verification_evidence from Step 6.

  • pass: continue.
  • needs_revision: apply Review Resolution, update through a fresh technical-designer invocation using the existing path and complete applied findings, then rerun Steps 6-7 for the affected boundary.
  • rejected: resolve technical governing-source conflicts through Review Resolution; ask the user only when confirmed outcome, desired-future requirements, and non-goals cannot all remain true and the user must choose which changes.

Invoke dev-workflows:design-sync for consistency with other Design Docs and apply Review Resolution to actionable conflicts. Report SKIPPED distinctly when only one Design Doc exists.

Present the Design Doc, accepted ADR paths, resolved limitations/declines, and design-sync result. [Stop: Design approval].

Completion Criteria

  • Scope and Structural Scale were confirmed from outcomes and responsibility boundaries.
  • ADRs exist only for decision points passing both filters, and the complete batch received one review and approval.
  • A Design Doc exists regardless of whether ADRs were needed.
  • Applicable existing-behavior, contract, assumption, equivalence, and verification safeguards reached the Design Doc.
  • Review Resolution routed only needs_revision issues into correction work.
  • All stop points received explicit user confirmation.

Related Skills

View on GitHub
GitHub Stars687
CategoryAI
Updated5d ago
Forks104

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions