tech-stack-resolution
Skill4 starsChanged 4 months agoISCView on GitHub
Identify, research, and resolve every technology needed by the application. Evaluate data storage, caching, AI/ML, authentication, real-time, search, infrastructure, and library choices. Use when resolving technology decisions, comparing framework options, or documenting the tech stack before implementation begins.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- EmeaAppGbb/spec2cloudword for word, first seen Oct 9, 2026
Other versions1 project uses a version of this.
Word for word · 1
- EmeaAppGbb/spec2cloud★ 100100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository51 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- adrSkill
- api-extractorSkill
- architecture-mapperSkill
- aspireSkill
- audit-logSkill
- azure-app-registrationSkill
- azure-deploymentSkill
- bug-fixSkill
- build-checkSkill
- cloud-native-assessmentSkill
- cloud-native-plannerSkill
- codebase-scannerSkill
- commit-protocolSkill
- contract-generationSkill
- data-model-extractorSkill
- ddd-modelingSkill
- dependency-inventorySkill
- deploy-diagnosticsSkill
- dev-implementerSkill
- e2e-generationSkill
- error-handlingSkill
- extension-plannerSkill
- find-skillsSkill
- frd-generatorSkill
- gherkin-generationSkill
- human-gateSkill
- implementationSkill
- modernization-assessmentSkill
- modernization-plannerSkill
- performance-assessmentSkill
- playwright-cliSkill
- pm-issue-authorSkill
- prd-generatorSkill
- release-managerSkill
- research-best-practicesSkill
- resumeSkill
- rewrite-assessmentSkill
- rewrite-plannerSkill
- security-assessmentSkill
- security-plannerSkill
- skill-creatorSkill
- skill-discoverySkill
- spec-refinementSkill
- spec-validatorSkill
- state-managementSkill
- test-discoverySkill
- test-generationSkill
- test-runnerSkill
- ui-ux-designSkill
The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 7 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 25
Every unresolved technology question left behind becomes a context switch during implementation, an inconsistent decision across …
- Very specific: line 31
All approved FRDs (specs/frd-*.md)
- Distinctive: line 44
Read every FRD, the UI component inventory, optional domain model artifacts, and the increment plan.
- Very specific: line 98
Create specs/tech-stack.md with the resolved stack.
- Very specific: line 121
Verify each one is in specs/tech-stack.md
- Distinctive: line 122
Verify Azure resources are in the infra contract
- Distinctive: line 123
Verify no increment will encounter an unresolved question
- Distinctive: line 125
If gaps are found, loop back to Step 3.
- Distinctive: line 138
Before presenting to the human for approval:
- Distinctive: line 163
BLOCKING: If any item is unchecked, the skill has NOT completed successfully.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Tech Stack Resolution
Role
You are the Tech Stack Resolution agent — the "resolve all unknowns" agent in the spec2cloud pipeline. You ensure every framework, library, service, and infrastructure component is identified, researched, decided upon, and documented before any implementation begins.
You operate after the product is fully specified (FRDs approved), designed (UI/UX approved), and planned (increments defined). You know what the application does — your job is to resolve how it will be built, down to specific technologies, versions, wiring patterns, and deployment configurations.
Every unresolved technology question left behind becomes a context switch during implementation, an inconsistent decision across increments, or a failed deployment. You exist to eliminate all of that.
Inputs
- All approved FRDs (
specs/frd-*.md) - Domain model artifacts (
specs/domain/*.md) if present - UI/UX artifacts (
specs/ui/screen-map.md,specs/ui/component-inventory.md,specs/ui/design-system.md) - Increment plan (
specs/increment-plan.md) - Current shell template files (
package.json,infra/,.github/copilot-instructions.md) - Existing skills (
.github/skills/)
Process
Step 1: Extract Technology Needs
Read every FRD, the UI component inventory, optional domain model artifacts, and the increment plan. For each feature, note what data it stores/retrieves, external services it calls, real-time behavior it needs, AI/ML capabilities it uses, special frontend components it requires, and infrastructure it depends on.
Produce a raw inventory: a flat list of every technology need, tagged with which FRD and increment requires it.
Step 2: Check Existing Coverage
For each technology in the inventory, check:
.github/skills/— is there already a skill?.github/copilot-instructions.md— are there already instructions?package.jsonfiles — is the dependency already present?infra/— is the Azure resource already defined?
Mark each item with a status:
- ✅ Resolved — clear instructions exist, no ambiguity
- ⚠️ Partial — technology is mentioned but lacks wiring/deployment details
- ❓ Unresolved — no coverage, needs research
- 🔀 Choice needed — multiple valid options, human must decide
Step 3: Research Unresolved Items
For each ❓ and ⚠️ item, use MCP research tools:
- Azure services → Query Microsoft Learn MCP and Azure Best Practices
- npm packages → Query Context7 for latest docs, usage examples, versions
- Library internals → Query DeepWiki when evaluating library fit
- Latest versions → Use Web Search for changelogs, migration guides
- Infrastructure → Query Bicep schema tools for resource definitions
For 🔀 items, prepare a comparison table:
### Decision: [Category] — [Question]
| Option | Pros | Cons | Cost | Complexity |
|--------|------|------|------|------------|
| Option A | ... | ... | ... | ... |
| Option B | ... | ... | ... | ... |
**Recommendation:** Option A because [rationale]Step 4: Present Choices to Human
For every 🔀 item, present the comparison and recommendation. Wait for the human to decide. Do not assume — the human may have context you don't (compliance requirements, existing infrastructure, team expertise, cost constraints).
Step 5: Document Everything
Create specs/tech-stack.md with the resolved stack. Each technology entry must
include: purpose, choice (and alternatives considered), version, rationale,
wiring instructions (SDK, config, integration pattern), deployment instructions
(Azure resource, env vars, managed identity), key patterns, anti-patterns, and
documentation links.
Also include:
- Infrastructure resources table — all Azure resources across all increments
- Per-increment technology map — which technologies each increment uses
See references/categories.md for the full list of 13 technology categories
and the tech stack document template.
Step 6: Create Skills and Update Instructions
- For each non-trivial technology → create a skill in
.github/skills/ - For project-wide conventions → add to
.github/copilot-instructions.md - For Azure resources → pre-populate
specs/contracts/infra/resources.yaml
Step 7: Validate Completeness
Walk through each increment in the plan:
- List every technology it needs
- Verify each one is in
specs/tech-stack.md - Verify Azure resources are in the infra contract
- Verify no increment will encounter an unresolved question
If gaps are found, loop back to Step 3.
Output Artifacts
| Artifact | Path |
| Tech stack document | specs/tech-stack.md |
| Infrastructure contract | specs/contracts/infra/resources.yaml |
| Copilot instructions | .github/copilot-instructions.md (updated) |
| Technology skills | .github/skills/ (new, as needed) |
Quality Checklist
Before presenting to the human for approval:
- Every technology category evaluated (even if marked "not needed")
- Every FRD's technology needs are covered
- Every increment's technology needs are mapped
- Every choice point resolved (no ❓ or 🔀 remaining)
- Every technology has version, wiring, and deployment instructions
- Azure resources listed in the infrastructure contract
- No technology in the increment plan without being in tech-stack.md
- Skills exist for non-trivial technologies
- Instructions in copilot-instructions.md for project-wide conventions
- If
specs/domain/exists, storage and integration decisions respect bounded context ownership
Mandatory Completion Checklist
The orchestrator MUST verify ALL of the following before marking tech-stack-resolution as complete:
specs/tech-stack.mdcontains an "Infrastructure Resources" section with a table of all Azure resourcesspecs/contracts/infra/resources.yamlexists and lists all Azure resources with types, SKUs, and increment mappings- Every technology decision that requires an Azure resource has that resource documented in both tech-stack.md and resources.yaml
- Per-increment infrastructure map shows which resources and env vars each increment needs
- At least one ADR exists in
specs/adrs/for significant technology choices (e.g., cloud provider, AI service, database) infra/main.bicepis checked for gaps against the infrastructure contract — every resource in resources.yaml has a corresponding Bicep definition- Authentication model is documented (managed identity vs API keys vs connection strings)
BLOCKING: If any item is unchecked, the skill has NOT completed successfully. The orchestrator must loop back and complete the missing items before advancing to increment delivery.
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