Skill Seekers

Prerequisites

pip install skill-seekers

Or: uv pip install skill-seekers

Commands

Source Command

Local code skill-seekers-codebase --directory ./path

Docs URL skill-seekers scrape --url https://...

GitHub skill-seekers github --repo owner/repo

PDF skill-seekers pdf --file doc.pdf

Quick Start

Analyze local codebase

skill-seekers-codebase --directory /path/to/project --output output/my-skill/

Package for Claude

yes | skill-seekers package output/my-skill/ --no-open

Options

Flag Description

--depth surface/deep/full

Analysis depth

--skip-patterns

Skip pattern detection

--skip-test-examples

Skip test extraction

--ai-mode none/api/local

AI enhancement

Skill_Seekers Codebase

Description

Local codebase analysis and documentation generated from code analysis.

Path: /home/lyh/Documents/Skill_Seekers

Files Analyzed: 140 Languages: Python Analysis Depth: deep

When to Use This Skill

Use this skill when you need to:

• Understand the codebase architecture and design patterns

• Find implementation examples and usage patterns

• Review API documentation extracted from code

• Check configuration patterns and best practices

• Explore test examples and real-world usage

• Navigate the codebase structure efficiently

⚡ Quick Reference

Codebase Statistics

Languages:

• Python: 140 files (100.0%)

Analysis Performed:

• ✅ API Reference (C2.5)

• ✅ Dependency Graph (C2.6)

• ✅ Design Patterns (C3.1)

• ✅ Test Examples (C3.2)

• ✅ Configuration Patterns (C3.4)

• ✅ Architectural Analysis (C3.7)

🎨 Design Patterns Detected

From C3.1 codebase analysis (confidence > 0.7)

• Factory: 44 instances

• Strategy: 28 instances

• Observer: 8 instances

• Builder: 6 instances

• Command: 3 instances

Total: 90 high-confidence patterns

See references/patterns/ for complete pattern analysis

📝 Code Examples

High-quality examples extracted from test files (C3.2)

Workflow: test full join multigraph (complexity: 1.00)

G = nx.MultiGraph() G.add_node(0) G.add_edge(1, 2) H = nx.MultiGraph() H.add_edge(3, 4) U = nx.full_join(G, H) assert set(U) == set(G) | set(H) assert len(U) == len(G) + len(H) assert len(U.edges()) == len(G.edges()) + len(H.edges()) + len(G) * len(H) U = nx.full_join(G, H, rename=('g', 'h')) assert set(U) == {'g0', 'g1', 'g2', 'h3', 'h4'} assert len(U) == len(G) + len(H) assert len(U.edges()) == len(G.edges()) + len(H.edges()) + len(G) * len(H) G = nx.MultiDiGraph() G.add_node(0) G.add_edge(1, 2) H = nx.MultiDiGraph() H.add_edge(3, 4) U = nx.full_join(G, H) assert set(U) == set(G) | set(H) assert len(U) == len(G) + len(H) assert len(U.edges()) == len(G.edges()) + len(H.edges()) + len(G) * len(H) * 2 U = nx.full_join(G, H, rename=('g', 'h')) assert set(U) == {'g0', 'g1', 'g2', 'h3', 'h4'} assert len(U) == len(G) + len(H) assert len(U.edges()) == len(G.edges()) + len(H.edges()) + len(G) * len(H) * 2

Instantiate DataFrame: See gh-7407 (complexity: 1.00)

df = pd.DataFrame([[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1], [0, 0, 0, 0]], index=[1010001, 2, 1, 1010002], columns=[1010001, 2, 1, 1010002])

test edge removal (complexity: 1.00)

embedding_expected.set_data({1: [2, 7], 2: [1, 3, 4, 5], 3: [2, 4], 4: [3, 6, 2], 5: [7, 2], 6: [4, 7], 7: [6, 1, 5]}) assert nx.utils.graphs_equal(embedding, embedding_expected)

Instantiate Graph: test graph1 (complexity: 1.00)

G = nx.Graph([(3, 10), (2, 13), (1, 13), (7, 11), (0, 8), (8, 13), (0, 2), (0, 7), (0, 10), (1, 7)])

Instantiate Graph: test graph2 (complexity: 1.00)

G = nx.Graph([(1, 2), (4, 13), (0, 13), (4, 5), (7, 10), (1, 7), (0, 3), (2, 6), (5, 6), (7, 13), (4, 8), (0, 8), (0, 9), (2, 13), (6, 7), (3, 6), (2, 8)])

Configuration example: test davis birank (complexity: 1.00)

answer = {'Laura Mandeville': 0.07, 'Olivia Carleton': 0.04, 'Frances Anderson': 0.05, 'Pearl Oglethorpe': 0.04, 'Katherina Rogers': 0.06, 'Flora Price': 0.04, 'Dorothy Murchison': 0.04, 'Helen Lloyd': 0.06, 'Theresa Anderson': 0.07, 'Eleanor Nye': 0.05, 'Evelyn Jefferson': 0.07, 'Sylvia Avondale': 0.07, 'Charlotte McDowd': 0.05, 'Verne Sanderson': 0.05, 'Myra Liddel': 0.05, 'Brenda Rogers': 0.07, 'Ruth DeSand': 0.05, 'Nora Fayette': 0.07, 'E8': 0.11, 'E7': 0.09, 'E10': 0.07, 'E9': 0.1, 'E13': 0.05, 'E3': 0.07, 'E12': 0.07, 'E11': 0.06, 'E2': 0.05, 'E5': 0.08, 'E6': 0.08, 'E14': 0.05, 'E4': 0.06, 'E1': 0.05}

Configuration example: test davis birank with personalization (complexity: 1.00)

answer = {'Laura Mandeville': 0.29, 'Olivia Carleton': 0.02, 'Frances Anderson': 0.06, 'Pearl Oglethorpe': 0.04, 'Katherina Rogers': 0.04, 'Flora Price': 0.02, 'Dorothy Murchison': 0.03, 'Helen Lloyd': 0.04, 'Theresa Anderson': 0.08, 'Eleanor Nye': 0.05, 'Evelyn Jefferson': 0.09, 'Sylvia Avondale': 0.05, 'Charlotte McDowd': 0.06, 'Verne Sanderson': 0.04, 'Myra Liddel': 0.03, 'Brenda Rogers': 0.08, 'Ruth DeSand': 0.05, 'Nora Fayette': 0.05, 'E8': 0.11, 'E7': 0.1, 'E10': 0.04, 'E9': 0.07, 'E13': 0.03, 'E3': 0.11, 'E12': 0.04, 'E11': 0.03, 'E2': 0.1, 'E5': 0.11, 'E6': 0.1, 'E14': 0.03, 'E4': 0.06, 'E1': 0.1}

test junction tree directed confounders (complexity: 1.00)

J.add_edges_from([(('C', 'E'), ('C',)), (('C',), ('A', 'B', 'C')), (('A', 'B', 'C'), ('C',)), (('C',), ('C', 'D'))]) assert nx.is_isomorphic(G, J)

test junction tree directed cascade (complexity: 1.00)

J.add_edges_from([(('A', 'B'), ('B',)), (('B',), ('B', 'C')), (('B', 'C'), ('C',)), (('C',), ('C', 'D'))]) assert nx.is_isomorphic(G, J)

test junction tree undirected (complexity: 1.00)

J.add_edges_from([(('A', 'D'), ('A',)), (('A',), ('A', 'C')), (('A', 'C'), ('C',)), (('C',), ('B', 'C')), (('B', 'C'), ('C',)), (('C',), ('C', 'E'))]) assert nx.is_isomorphic(G, J)

See references/test_examples/ for all extracted examples

⚙️ Configuration Patterns

From C3.4 configuration analysis

Configuration Files Analyzed: 23 Total Settings: 165 Patterns Detected: 0

Configuration Types:

• unknown: 23 files

See references/config_patterns/ for detailed configuration analysis

📚 Available References

This skill includes detailed reference documentation:

• API Reference: references/api_reference/

• Complete API documentation

• Dependencies: references/dependencies/

• Dependency graph and analysis

• Patterns: references/patterns/

• Detected design patterns

• Examples: references/test_examples/

• Usage examples from tests

• Configuration: references/config_patterns/

• Configuration patterns

Generated by Skill Seeker | Codebase Analyzer with C3.x Analysis