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Dt Methods

MicrosoftOfficialPublished by Microsoft

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  • Business and productivity
  • MIT
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From the author

Design Thinking method coaching knowledge across all nine methods including per-method techniques, deep expertise, and industry context (energy, financial services, healthcare, manufacturing, nonprofit and social impact, pharmaceuticals and life sciences, professional services, public sector, retail and CPG)
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The dt-methods skill provides a structured reference system for AI agents to coach teams through the Design Thinking process. It organizes guidance into three layers: core method references for day-to-day activities, deep references for advanced facilitation and recovery, and industry-specific context to tailor vocabulary and constraints. The skill covers nine major industries, including energy, healthcare, and financial services, ensuring that coaching is grounded in the specific operational realities and regulatory environments of the user's sector.

What it does

  • Provides step-by-step guidance for nine core Design Thinking methods.
  • Offers advanced facilitation techniques and recovery strategies for complex scenarios.
  • Maps Design Thinking concepts to industry-specific terminology and constraints.
  • Integrates telemetry expectations for session artifacts to ensure observable outcomes.
  • Supplies industry-specific empathy tools and stakeholder considerations.
  • Supports tailoring of coaching based on the active method and identified industry context.

When to use it

  • When facilitating a Design Thinking session and requiring method-specific guidance.
  • When a team needs advanced troubleshooting or recovery techniques during a workshop.
  • When applying Design Thinking within a specific industry to ensure relevant vocabulary and constraints are respected.
  • When defining telemetry or audit trails for Design Thinking session artifacts.

Advantages

  • Ensures consistent coaching across the entire Design Thinking lifecycle.
  • Reduces friction by using industry-appropriate language and concepts.
  • Provides a clear path for scaling from basic methods to advanced facilitation.
  • Integrates operational and regulatory awareness into the design process.

Usage examples

“How should I facilitate a brainstorming session for a team in the energy sector?”
The agent will load the brainstorming method reference and the energy industry context, providing guidance that uses energy-specific terms like 'reliability concern' and 'forced outage rate' while emphasizing safety and regulatory constraints.
“We are stuck during the user research phase; what advanced techniques can we use?”
The agent will access the deep reference for the Design Research method to provide advanced facilitation strategies and recovery techniques to help the team overcome their current roadblock.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/dt-methods/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip dt-methods.zip -d .agents/skills

Documentation by Microsoft

Design Thinking Methods Skill

Entrypoint for Design Thinking method coaching knowledge. The dt-coach agent loads the method reference matching the active method in coaching state, the matching deep reference when advanced technique is needed, and the industry reference when an industry context applies.

How to use this skill

  • Read the method reference for the method currently active in coaching state to ground day-to-day coaching.

  • Read the matching deep reference when the conversation needs advanced facilitation, recovery techniques, or expert frameworks beyond the core method guidance.

  • Read the industry reference when the team has identified one of the nine covered industries as their context, and weave its vocabulary, constraints, and empathy tools into method-specific guidance.

  • Read dt-coach-telemetry.md when DT session artifacts need observable telemetry expectations grounded in telemetry-foundations.

Method references

Industry context references

Load the matching reference when the team identifies its industry context.

ReferenceWhen to load
industry-energy.mdEnergy-sector vocabulary, constraints, empathy tools, and reference scenario.
industry-financial-services.mdFinancial services vocabulary, constraints, empathy tools, and reference scenario.
industry-healthcare.mdHealthcare vocabulary, constraints, empathy tools, and reference scenario.
industry-manufacturing.mdManufacturing vocabulary, constraints, empathy tools, and reference scenario.
industry-nonprofit-social-impact.mdNonprofit and social impact vocabulary, constraints, empathy tools, and reference scenario.
industry-pharmaceuticals-life-sciences.mdPharmaceuticals and life sciences vocabulary, constraints, empathy tools, and reference scenario.
industry-professional-services.mdProfessional services vocabulary, constraints, empathy tools, and reference scenario.
industry-public-sector.mdPublic sector and government vocabulary, constraints, empathy tools, and reference scenario.
industry-retail-cpg.mdRetail and consumer goods vocabulary, constraints, empathy tools, and reference scenario.

Skill layout

.
├── SKILL.md
└── references/
    ├── method-01-scope.md
    ├── method-01-deep.md
    ├── method-02-research.md
    ├── method-02-deep.md
    ├── method-03-synthesis.md
    ├── method-03-deep.md
    ├── method-04-brainstorming.md
    ├── method-04-deep.md
    ├── method-05-concepts.md
    ├── method-05-deep.md
    ├── method-06-lofi-prototypes.md
    ├── method-06-deep.md
    ├── method-07-hifi-prototypes.md
    ├── method-07-deep.md
    ├── method-08-testing.md
    ├── method-08-deep.md
    ├── method-09-iteration.md
    ├── method-09-deep.md
    ├── industry-energy.md
    ├── industry-financial-services.md
    ├── industry-healthcare.md
    ├── industry-manufacturing.md
    ├── industry-nonprofit-social-impact.md
    ├── industry-pharmaceuticals-life-sciences.md
    ├── industry-professional-services.md
    ├── industry-public-sector.md
    ├── industry-retail-cpg.md
    └── dt-coach-telemetry.md

Files

references/method-03-synthesis.md


title: 'DT Method 03: Input Synthesis' description: Design Thinking Method 03 (Input Synthesis) for clustering research signals into insights and opportunity areas.

Input synthesis aggregates research inputs (interviews, surveys, reports, observations) to find patterns, themes, and insights that form a complete picture of the problem. Without proper synthesis, teams move to brainstorming with fragmented understanding instead of unified problem clarity.

Purpose

Transform fragmented research data from diverse sources into unified problem understanding that sets clear direction for solution development.

Sub-Method Phases

Phase 1: Synthesis Planning

Organize all Method 2 research outputs and establish the synthesis strategy. Determine data source availability, identify coverage gaps, and define the analysis approach.

Exit criteria: an input inventory exists cataloging all Method 2 artifacts with source type, coverage assessment, and a defined synthesis approach.

Phase 2: Synthesis Execution

Perform systematic pattern recognition across organized inputs. Identify cross-source themes, validate patterns through multiple perspectives, and develop unified insights.

Exit criteria: affinity clusters and insight statements exist with each theme supported by evidence from multiple independent sources.

Phase 3: Synthesis Documentation

Formalize validated patterns into structured problem definitions, insight statements, and how-might-we questions. Run synthesis validation across all five dimensions before declaring transition readiness.

Exit criteria: problem definition and how-might-we artifacts exist, five-dimension validation shows strength across all dimensions, and the team confirms shared problem understanding.

Coaching Hats

Two specialized hats activate based on conversation context. See method-03-deep.md for detailed hat guidance, activation triggers, coaching focus areas, and Human-AI Collaboration patterns.

HatRoleActivation
Pattern AnalystData organization, cross-source theme discovery, evidence-based validationRaw data shared, clustering needed, contradictions detected
Insight FramerProblem articulation, HMW questions, transition readiness assessmentPatterns validated, problem framing needed, transition discussion

Pattern Recognition Framework

Data Source Integration
  • Combine input sources: worker interviews revealing capability constraints, observational data showing environmental factors, performance reports quantifying impact metrics

  • Look for themes that emerge when different data sources confirm and reinforce each other

Theme Development
  • Individual insight: a specific observation or quote from one source

  • Supporting evidence: confirmation from additional sources and perspectives

  • Unified theme: the pattern connecting all perspectives into a coherent problem statement

  • Actionable direction: framing that guides solution development without prescribing specific solutions

Systematic Synthesis Process

Input Organization
  • Stakeholder inputs: interview transcripts, conversation notes, survey responses, stakeholder mapping

  • Observational data: workflow documentation, process mapping, environmental constraint analysis

  • Quantitative data: performance metrics, operational analytics, resource utilization

Pattern Recognition
  • Validate patterns through different stakeholder perspectives

  • Connect qualitative observations with quantitative metrics

  • Require multiple independent sources to support each theme before considering it robust

Unified Insight Development
  • Prioritize themes based on stakeholder impact and solution potential

  • Frame insights as actionable direction without prescribing specific solutions

  • Validate synthesis against original research data for accuracy

Synthesis Validation

Before transitioning to brainstorming, evaluate synthesis quality across five dimensions.

  • Research fidelity: synthesis accurately reflects collected evidence rather than assumptions

  • Stakeholder completeness: themes include the full range of relevant stakeholder groups

  • Pattern robustness: patterns appear across multiple data points, not from isolated anecdotes

  • Actionability: outputs translate into clear problem statements that can guide solution work

  • Team alignment: the team shares common understanding and agrees synthesis reflects their learning

When validation reveals weaknesses: return to data sources for low fidelity, refine statements for weak actionability, conduct targeted research for completeness gaps, abandon themes for insufficient robustness.

Coaching Patterns

  • Every major theme requires evidence from multiple research sources

  • Include all key user groups; silent stakeholders often reveal critical constraints

  • Maintain domain-specific nuances while identifying universal patterns

  • Do not force themes that evidence does not genuinely support

Quality Rules

  • Seven red flags signal synthesis failure: Single Source Dependency, Stakeholder Blind Spots, Pattern Forcing, Solution Bias, Jargon Overload, Scope Creep, and Premature Convergence

  • Effective synthesis demonstrates multi-source validation, complete stakeholder representation, actionable insights, robust patterns, and preserved context

  • Test themes with the question: would original research participants recognize themselves in this synthesis?

Synthesis Goals

Accomplish
  • Multi-source pattern recognition across different research data types

  • Stakeholder perspective integration across all key user groups

  • Environmental context preservation including domain-specific constraints

  • Solution-ready problem statements without prescribing solutions

Avoid
  • Theme forcing where evidence does not support connections

  • Single source over-reliance

  • Premature solution jumping before completing synthesis

  • Context loss in pursuit of generic patterns

Success Indicators

During Synthesis
  • All research inputs systematically analyzed without data loss

  • Themes supported by multiple independent data sources

  • Environmental and contextual factors preserved

  • Team members demonstrate shared understanding

After Synthesis
  • Unified problem statements with stakeholder consensus

  • Validated themes supported by comprehensive evidence

  • Solution focus areas identified without premature solution prescription

  • Team alignment on problem understanding and design direction

Input from Method 2

  • User interview findings with direct quotes and observations

  • Environmental constraint documentation

  • Workflow integration requirements

  • Unmet need patterns across user groups

Output to Method 4

  • Clear problem focus areas with validated themes for solution development

  • Design constraints from environmental and contextual factors

  • Stakeholder priorities and specific needs for solution targeting

  • Success criteria based on synthesized problem understanding

Artifacts

Method 3 artifacts at .copilot-tracking/dt/{project-slug}/method-03-synthesis/:

  • affinity-clusters.md: labeled clusters with representative evidence and tensions

  • insight-statements.md: synthesized insights explaining why patterns matter, with supporting sources and design implications

  • problem-definition.md: unified problem framing with scope, stakeholders, constraints, and success signals

  • how-might-we-questions.md: HMW questions bridging from problem understanding to ideation, with related insights and constraints

Problem-to-Solution Space Transition

Method 3 sits at the boundary between Problem Space and Solution Space. This is the most critical transition. Moving to solutions without validated problem understanding produces solutions to the wrong problem.

Transition readiness signals:

  • Synthesis validation shows strength across all five dimensions with remaining gaps explicitly acknowledged

  • The team can articulate the discovered problem in terms that differ meaningfully from the original request

  • Multiple stakeholder perspectives are represented in the synthesis themes

  • Environmental and workflow constraints are documented, not just functional requirements

Next-step pathways:

  • Proceed to Method 4 when synthesis artifacts are complete and stable

  • Hand off to the RPI workflow through the Problem Space exit procedure in the dt-rpi-integration skill when the team wants a Researcher/Planner/Implementor to continue from validated problem understanding

  • Return to Methods 1-2 when synthesis exposes research gaps, conflicting narratives, or missing constraints

  • All DT coaching artifacts are scoped to .copilot-tracking/dt/{project-slug}/. Never write DT artifacts directly under .copilot-tracking/dt/ without a project-slug directory.

Requirements and compatibility

Written for: GitHub Copilot, Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

Security

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Attribution and licence

Published by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/hve-core · .github/skills/design-thinking/dt-methods · commit f425e94
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download dt-methods.zip