# Analyze Your Stack and Recommend Skills

Project teams may miss relevant AI development skills for their frameworks and workflows. This skill maps detected technologies to recommendations and optional project templates.

## Install

```bash
npx skillstore add consiliency/stack-analyzer
```

## Metadata

- Status: approved
- Slug: consiliency-stack-analyzer
- Skillstore revision: r1
- Version status: missing
- Tree hash: cfe6120bf8110b1e4b5846c499520b8f28c835515134840bf7ae8adbcca993a5
- Author: Consiliency
- GitHub username: Consiliency
- License: MIT
- Repository: https://github.com/Consiliency/treesitter-chunker/tree/main/.ai-dev-kit/skills/stack-analyzer
- Ref: 635f69fb8d2f4e6330ba47a4e5a0fb239c04d110
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network, filesystem
- Quality score: 69
- Public page: https://skillstore.pages.dev/skills/consiliency-stack-analyzer
- Manifest: https://skillstore.pages.dev/api/skills/consiliency-stack-analyzer/manifest

## Capabilities

- Uses library-detection results to identify languages, frameworks, databases, testing tools, and build tools.
- Matches detected files and dependencies against configurable skill activation rules.
- Ranks recommendations with high, medium, and low priorities.
- Produces a Markdown report with detected technologies, recommendations, reasons, and activation status.
- Can scaffold research, domain, and testing skill templates and track generated files in a manifest.

## Use Cases

- Audit an Existing Repository: Review detected technologies and receive evidence-based skill recommendations before changing the project.
- Standardize Team AI Skills: Compare repositories against shared recommendation rules and identify consistent development guidance.
- Bootstrap Project Guidance: Plan project-specific research, domain, and testing skills with tracked output paths.

## Prompt Templates

### List Recommendations

```
Analyze this repository's detected stack and list recommended generic skills. Do not change files.
```

### Explain Rule Matches

```
Compare detected dependencies and paths with recommendation rules. Explain each match and flag uncertain recommendations.
```

### Plan Project Scaffolds

```
Prepare a scaffold plan for research, domain, and testing skills. Show target paths and required customizations without writing files.
```

### Review Full Activation Plan

```
Rank recommendations, identify missing templates, and propose a reviewed manifest update. Require confirmation before every repository change.
```

## Limitations

- Depends on the separate library-detection skill for stack discovery.
- Recommendation quality depends on file and dependency rules in the bundled configuration.
- Scaffolding changes repository files and should require explicit review before execution.
- The configured project-api template is not included in this package.

## Best Practices

- Run report-only analysis before enabling activation or scaffolding.
- Review every detection match and remove recommendations unsupported by repository evidence.
- Commit or back up repository changes before creating project-specific skills.

## Anti Patterns

- Do not scaffold templates before reviewing target paths and generated names.
- Do not trust recommendations when detection evidence is missing or stale.
- Do not run shell examples with unvalidated project names or target paths.

## Security Audit

- Audited at: 2026-07-19T04:22:58.63\+00:00
- Summary: Most static alerts are false positives caused by Markdown backticks, code fences, path examples, and table text. The scaffolding workflow executes shell commands and writes into the target repository. Its unscoped move can overwrite SKILL.md in the current directory, so the workflow needs safer path handling.

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