Agent Skills Pipeline v1.0

8-stage pipeline: Scout → Filter → Reader → Extractor → Score → Generator → Reviewer → Publisher
- Scout: GitHub search with token auth + rate limit retry
- Filter: Deterministic rules (language, stars, age, keywords)
- Reader: Incremental context loading (README → docs → examples → code)
- Extractor: LLM workflow extraction with JSON retry
- Score: Rule-based evaluation (no LLM)
- Generator: Standardized Hermes Skill format
- Reviewer: Independent LLM review (separate from generator)
- Publisher: Branch + PR to Gitea

First run: 5 repos discovered, 0 extracted (correct — all frameworks, no workflows)
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# Agent Skills Pipeline Configuration
gitea:
base_url: http://localhost:3000
token: "b721b5f288d227e9336241f95319437ab40256d6"
owner: tonyjbala
repo: agent-skills
clone_url: http://localhost:3000/tonyjbala/agent-skills.git
github:
token: "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"
llm:
base_url: http://100.64.0.2:8083/v1
model: /home/ty/models/qwen36-27b-mtp-gguf/Qwen3.6-27B-UD-Q4_K_XL.gguf
api_key: ""
max_tokens: 8000
scout:
queries:
- 'agent framework langgraph mcp multi-agent'
- 'ai workflow agent pipeline rag pipeline'
- 'llm orchestration tool-use tool calling'
filters:
stars_min: 10
pushed_after: 2026-06-01
language: Python
archived: false
max_results: 30
cooldown_hours: 24
filter:
categories:
keep:
- "AI Agent"
- "Machine Learning"
- "NLP"
- "Data Processing"
- "DevOps"
- "Web Framework"
reject:
- "CSS"
- "JavaScript"
- "HTML"
- "Game"
- "Dataset"
min_stars: 10
max_age_days: 365
reader:
max_files: 5
max_tokens_per_file: 40000
extractor:
min_steps: 3
required_fields:
- goal
- inputs
- steps
- outputs
scoring:
min_score: 0.85
checks:
- readme_exists
- examples_exist
- min_steps
- reusable
- general_purpose
generator:
output_format: hermes_skill
reviewer:
confidence_min: 0.80
publisher:
branch_prefix: "skill/"
assign_reviewer: ""