Individual skill
apexcloud-retention-ops
Build exact JSON-only reports from the ApexCloud Retention Operations API. Use when a prompt mentions ApexCloud retention data, task environment API calls, account metrics, billing, support tickets, NPS, A/R aging, opportunities, HR summary, event performance, churn exports, renewal risk queues, QBR packets, receivables reviews, retention boards, or any similar structured business output that must match an answer template and controlled label vocabulary.
experiments/codex_skill_creator_comparison_gpt5_5_xhigh/reports/skills/task_group_004/fewshot/cc/fewshot_attempt_01/SKILL.md
Source commit 5082a777379156a048881e94940d640702e5e09a
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- Yes
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- No
- Repository scan complete
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- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- Last checked
- Nov 6, 2026
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Repository context
- Repository stars (not skill ratings)
- 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.
- agent Repository topic
- ai Repository topic
- benchmark Repository topic
- llm Repository topic
- self-evolving Repository topic
- self-learning Repository topic
- skills Repository topic
- operations Derived category
- data Derived category
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SKILL.mdcore · 1,968 bytesreferences/api_patterns.mddoc · 2,211 bytes
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# ApexCloud Retention Ops
Use this skill for the staged ApexCloud reporting tasks.
## Workflow
1. Read the prompt and the answer template first. Treat the template as the contract for keys, nesting, item order, and allowed enum values.
2. Identify the report family and requested slice. Read [references/api_patterns.md](references/api_patterns.md) when the prompt combines multiple data sources or the endpoint mapping is not obvious.
3. Fetch only the needed records from the local task environment described in `environment_access.md`.
4. Build a local fact table from the live data, then calculate the requested rankings, summaries, or validation metrics.
5. Keep every controlled label exactly as written in the prompt or template. Do not invent synonyms or widen the vocabularies.
6. Normalize the final JSON:
- currency: 2 decimals
- percentages: precision requested by the prompt