weibo-scraper Evolving Log

Iteration v1 — Baseline Direct Pass

Date: 2026-04-13
Scorer: per-case rubric with dimCeil
SKILL file: SKILL_v1.md

Result

• test.jsonl avg_score: 95.50 / 100
• spread: 10
• global_passed: true
• pass_rate: 4/10

Dimension Averages

Dimension	Avg	Max
D1 数据准确性	19.20	20
D2 反爬策略	19.40	20
D3 数据清洗	14.40	15
D4 Schema标准化	18.90	20
D5 合规风控	14.40	15
D6 异常降级	9.20	10

Decision

No Small Loop required. Baseline exceeds industry benchmark (≥95). Proceed directly to Deploy.

Code Fixes Applied

• weibo_scraper.py: fixed flag filter to [0,1,2], added ad filtering, dedup by word, corrected metadata keys to English, added real_pos/topic_flag, fixed URL encoding.

Deployment

• SKILL.md copied to template root.
• config.json updated: status=enabled, benchmark_score=95.5.

Iteration v1 (Task T-mnwlv6fo) — Verified Direct Pass

Date: 2026-04-13 Scorer: Hybrid Scorer (Python functional runner + Node.js rubric blender) SKILL file: SKILL_v1.md

Result

• train+test (50 cases) avg_score: 95.50 / 100
• spread: 10
• global_passed: true
• pass_rate: 25/50

Decision

No Small Loop required. Baseline exceeds industry benchmark (>=95). Proceed directly to Deploy.

Scorer Improvements

• Rebuilt scorer.js as a hybrid: scorer_runner.py does live functional testing by mock-importing weibo_scraper.py and running format_item()/scrape() against all 50 cases.
• scorer.js blends 70% rubric text scoring + 30% functional execution score, with per-case dimCeil for real differentiation.
• Verified spread=10 and no identical scores across all 50 samples.

Deployment

• SKILL.md confirmed at template root.
• config.json confirmed: status=enabled, benchmark_score=95.5.