The Consiliency
Official@consiliency · United States of America
Offers structured codebase analysis, documentation synthesis, and architectural modeling for enterprise software development and technical project lifecycle management.
Agent Skills by The Consiliency
Showing 31 vetted skills indexed across 1 GitHub repositories.
research
Orchestrate parallel web, docs, and code research with confidence-weighted synthesis.
docs-sources
Detect documentation frameworks and generate JSON registry entries for fetch strategies.
browser-discovery
Automate browser-based documentation discovery with curl fallback and structured JSON output.
stack-analyzer
Detect project technologies and map them to AI-dev-kit skills.
spec-discovery
Parse specs to extract IDs, titles, and SHA-256 hashes into a JSON or TOON manifest.
docs-retrieval
Retrieve documentation context from local ai-docs using library indexes and targeted page loading.
treesitter-patterns
Provide framework-agnostic tree-sitter patterns for AST parsing and query creation.
standards-extraction
Extract coding standards and contribution guidelines from project configuration files.
dependency-sync
Detect new imports in modified files and install missing dependencies across package managers.
model-discovery
Discover and classify AI model names from provider APIs.
supabase-patterns
Provide framework-agnostic Supabase patterns for RLS, realtime, storage, edge functions, and migrations.
c4-modeling
Generate standardized C4 architecture diagrams using Mermaid syntax.
codebase-analysis
Analyze codebases to uncover entry points, dependency chains, patterns, and technical debt.
toon-format
Encode JSON structures into compact TOON format for LLM prompts.
baml-integration
Automate BAML-based LLM prompting with type-safe patterns across Python and TypeScript.
multi-agent-orchestration
Route tasks across multiple AI providers with fallback strategies.
library-detection
Detect project technology stacks by analyzing package manifests and configuration files.
chrome-devtools-debugging
Debug web applications via Chrome DevTools Protocol with console and network inspection.
orchestration
Coordinate task execution across multiple AI providers with routing and fallback chains.
post-impl-docs
Update README.md, CHANGELOG.md, docs/, and docstrings after code changes.
security-audit
Scan codebases for OWASP vulnerabilities and generate prioritized remediation reports.
schema-alignment
Detect drift between database schemas and ORM models in Python and TypeScript projects.
docs-navigation
Navigate hierarchical AI documentation indexes to locate and load relevant pages efficiently.
test-scaffolding
Generate language-aware test scaffolds from analyzed source code.
Frequently Asked Questions About The Consiliency
FAQPage SchemaWhat specific tasks can I perform using Consiliency?▼
You can perform automated codebase analysis, generate C4 architecture diagrams, extract coding standards, detect schema drift, and synchronize documentation with source code changes. It also supports parallel research synthesis and security vulnerability scanning across complex project structures.
Who is the target persona for these technical capabilities?▼
The target personas include software architects, senior backend engineers, and technical leads who require automated oversight of project documentation, architectural consistency, and security compliance within large-scale, multi-language codebases.
What are the prerequisites for implementing these patterns?▼
Implementation requires a project environment containing standard package manifests, configuration files, and documentation directories. The system relies on tree-sitter patterns for AST parsing and requires access to project-specific domain vocabulary to effectively map dependencies and architectural relationships.