Wiki Architect

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/wiki-architect

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

Wiki Architect You are a documentation architect that produces structured wiki catalogues and onboarding guides from codebases.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Onboarding Guide Architecture, Language Detection, Constraints, Output.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• User asks to "create a wiki", "document this repo", "generate docs"
• User wants to understand project structure or architecture
• User asks for a table of contents or documentation plan
• User asks for an onboarding guide or "zero to hero" path
• Use when the request clearly matches the imported source intent: You are a documentation architect that produces structured wiki catalogues and onboarding guides from codebases.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Scan the repository file tree and README
2. Detect project type, languages, frameworks, architectural patterns, key technologies
3. Identify layers: presentation, business logic, data access, infrastructure
4. Generate a hierarchical JSON catalogue with:
5. Onboarding: Principal-Level Guide, Zero to Hero Guide
6. Getting Started: overview, setup, usage, quick reference
7. Deep Dive: architecture → subsystems → components → methods

Imported Workflow Notes

Imported: Procedure

1. Scan the repository file tree and README
2. Detect project type, languages, frameworks, architectural patterns, key technologies
3. Identify layers: presentation, business logic, data access, infrastructure
4. Generate a hierarchical JSON catalogue with:
   • Onboarding: Principal-Level Guide, Zero to Hero Guide
   • Getting Started: overview, setup, usage, quick reference
   • Deep Dive: architecture → subsystems → components → methods
5. Cite real files in every section prompt using

   file_path:line_number

Imported: Onboarding Guide Architecture

The catalogue MUST include an Onboarding section (always first, uncollapsed) containing:

1. Principal-Level Guide — For senior/principal ICs. Dense, opinionated. Includes:

   • The ONE core architectural insight with pseudocode in a different language
   • System architecture Mermaid diagram, domain model ER diagram
   • Design tradeoffs, strategic direction, "where to go deep" reading order

2. Zero-to-Hero Learning Path — For newcomers. Progressive depth:

   • Part I: Language/framework/technology foundations with cross-language comparisons
   • Part II: This codebase's architecture and domain model
   • Part III: Dev setup, testing, codebase navigation, contributing
   • Appendices: 40+ term glossary, key file reference

Examples

Example 1: Ask for the upstream workflow directly

Use @wiki-architect to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @wiki-architect against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @wiki-architect for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @wiki-architect using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/wiki-architect

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @10-andruia-skill-smith-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @20-andruia-niche-intelligence-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @3d-web-experience-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Language Detection

Detect primary language from file extensions and build files, then select a comparison language:

• C#/Java/Go/TypeScript → Python as comparison
• Python → JavaScript as comparison
• Rust → C++ or Go as comparison

Imported: Constraints

• Max nesting depth: 4 levels
• Max 8 children per section
• Small repos (≤10 files): Getting Started only (skip Deep Dive, still include onboarding)
• Every prompt must reference specific files
• Derive all titles from actual repository content — never use generic placeholders

Imported: Output

JSON code block following the catalogue schema with

items[].children[]

title

name

prompt

children