Individual skill
licensing-json-review
Build structured JSON answers for licensing-environment review tasks that use TASK_ENV_BASE_URL data. Use for contractor eligibility batches, restricted liquor-license staff packages, and alcohol renewal manual-review queues involving policies, applications, bonds, insurance, license history, violations, correspondence, inspections, settlements, privileges, incidents, site evidence, answer_template.json schemas, determinations, controls, verification gaps, or ranked queues.
experiments/codex_skill_creator_comparison_gpt5_5_xhigh/reports/skills/task_group_019/fewshot/deepagents/fewshot_attempt_01/SKILL.md
Source commit 5082a777379156a048881e94940d640702e5e09a
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- Yes
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- Yes
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- No
- Observed behavior
- Local scripts
- Last checked
- Nov 6, 2026
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- 121
- Repository last updated
- Oct 29, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
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SKILL.mdcore · 3,443 bytesSKILL.mdcore · 3,443 bytesSKILL.mdcore · 3,443 bytesSKILL.mdcore · 3,443 bytesreferences/decision-rules.mddoc · 11,773 bytesscripts/fetch_licensing_records.pyruns · 6,748 bytes
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# Licensing JSON Review
## Core Workflow
1. Read the prompt and `input/payloads/answer_template.json` first. Treat the template as the output contract: required keys, allowed enum values, ordering rules, date rules, and exact casing all come from it.
2. Extract target identifiers, target locations, review dates, boundary dates, queue size, and any special focus areas from the prompt.
3. Fetch only the records needed for those targets from `<TASK_ENV_BASE_URL>`. Use the helper if useful:
```bash
python skill/scripts/fetch_licensing_records.py --base-url "$TASK_ENV_BASE_URL" --family contractor --ids C-...
python skill/scripts/fetch_licensing_records.py --base-url "$TASK_ENV_BASE_URL" --family liquor --ids L-...
python skill/scripts/fetch_licensing_records.py --base-url "$TASK_ENV_BASE_URL" --family renewal --ids AL-...
```