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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)
80 lines
1.4 KiB
YAML
80 lines
1.4 KiB
YAML
# Agent Skills Pipeline Configuration
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gitea:
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base_url: http://localhost:3000
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token: "b721b5f288d227e9336241f95319437ab40256d6"
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owner: tonyjbala
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repo: agent-skills
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clone_url: http://localhost:3000/tonyjbala/agent-skills.git
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github:
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token: "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"
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llm:
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base_url: http://100.64.0.2:8083/v1
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model: /home/ty/models/qwen36-27b-mtp-gguf/Qwen3.6-27B-UD-Q4_K_XL.gguf
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api_key: ""
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max_tokens: 8000
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scout:
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queries:
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- 'agent framework langgraph mcp multi-agent'
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- 'ai workflow agent pipeline rag pipeline'
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- 'llm orchestration tool-use tool calling'
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filters:
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stars_min: 10
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pushed_after: 2026-06-01
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language: Python
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archived: false
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max_results: 30
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cooldown_hours: 24
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filter:
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categories:
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keep:
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- "AI Agent"
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- "Machine Learning"
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- "NLP"
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- "Data Processing"
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- "DevOps"
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- "Web Framework"
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reject:
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- "CSS"
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- "JavaScript"
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- "HTML"
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- "Game"
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- "Dataset"
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min_stars: 10
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max_age_days: 365
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reader:
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max_files: 5
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max_tokens_per_file: 40000
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extractor:
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min_steps: 3
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required_fields:
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- goal
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- inputs
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- steps
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- outputs
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scoring:
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min_score: 0.85
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checks:
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- readme_exists
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- examples_exist
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- min_steps
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- reusable
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- general_purpose
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generator:
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output_format: hermes_skill
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reviewer:
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confidence_min: 0.80
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publisher:
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branch_prefix: "skill/"
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assign_reviewer: ""
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