tech-stack-recommender
Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.
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Installation for Agentic Skill
View all platforms →skilz install alirezarezvani/claude-cto-team/tech-stack-recommender skilz install alirezarezvani/claude-cto-team/tech-stack-recommender --agent opencode skilz install alirezarezvani/claude-cto-team/tech-stack-recommender --agent codex skilz install alirezarezvani/claude-cto-team/tech-stack-recommender --agent gemini
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Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/alirezarezvani/claude-cto-team cp -r claude-cto-team/skills/tech-stack-recommender ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- alirezarezvani (GitHub)
- Repository
- claude-cto-team
- Type
- Technical
- Meta-Domain
- cloud infrastructure
- Primary Domain
- terraform
- Market Score
- 0.0
Agent Skill Grade
C
Score: 70/100
Click to see breakdown
Score Breakdown
Areas to Improve
- References two files that don't exist (framework-comparison.md, migration-playbooks.md), violating layered structure principle
- Four stack templates (120 lines) repeat similar structure; violates token economy and conciseness principles
- Decision framework shows inputs but lacks numbered step-by-step workflow for executing a recommendation
Recommendations
- Focus on improving Pda (currently 15/30)
- Address 2 high-severity issues first
- Add trigger phrases to description for discoverability
Graded: 1/24/2026
Developer Feedback
I've been poking around tech stack selection problems lately, and I see you're tackling the decision-making side of it—how did you land on this particular approach for guiding those choices?
Links:
The TL;DR
You're at 70/100, solidly in C territory. This is based on Anthropic's skill grading rubric across five pillars. Your strongest area is Spec Compliance (12/15)—the frontmatter and naming are clean. Weakest area is Progressive Disclosure Architecture (15/30)—you're packing 448 lines into a single file when you could be more strategic about layering content.
What's Working Well
- Clear decision framework (lines 20-41) with ASCII diagrams showing inputs and outputs—this actually gives people a visual anchor for how to use the skill
- Excellent stack templates (lines 187-307) that show real-world examples for SaaS, e-commerce, and enterprise scenarios—people can see themselves in these
- Strong metadata and triggers in the frontmatter—terms like "selecting frameworks," "language selection," and "infrastructure choices" are solid discovery hooks
- Practical evaluation checklist (lines 327-348) that gives people a way to validate their choice after the fact
The Big One: Missing Reference Files
You're listing two reference files that don't actually exist: framework-comparison.md and migration-playbooks.md (lines 444-447). This is a PDA violation because you're claiming a layered structure you haven't actually built.
Here's the fix: Either create those files and move your detailed comparison content into them, or remove the References section. If you go with creating them, you'd move those 4 stack templates (120 lines of repetition) into references/stack-templates.md and link to it. That alone would free up space and fix your token economy. Potential gain: +5 points.
Other Things Worth Fixing
Template repetition is eating your token budget (lines 185-307)—four nearly identical 30-line templates with the same structure (Frontend, Backend, Database, DevOps). Keep one in-SKILL.md example, move the rest to a reference file. +3 points.
No step-by-step workflow exists—you show a decision framework diagram but not numbered steps for how someone actually uses it. Add something like: "1. Gather requirements → 2. Assess team factors → 3. Match to Quick Stack table → 4. Validate trade-offs." +2 points.
Mixed voice and tense throughout—line 8 says "Provides structured recommendations" (declarative), but lines 330-332 use questions ("Current skills alignment?"). Pick one voice and stick with it. +1 point.
No feedback loop for validation—the checklist exists, but there's no guidance on what to do if the recommendation isn't working. Add a simple section: "If adoption is slow, assess learning curve; if performance lags, revisit database choice." +2 points.
Quick Wins
- Create
framework-comparison.mdandmigration-playbooks.mdfiles with existing content - Move the 4 stack templates to a reference file (keep 1 example in SKILL.md)
- Add numbered workflow steps after the decision framework
- Standardize to imperative voice throughout
- Add a "What to do if it's not working" section
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