Individual skill

portfolio-mgmt

Solve test-environment portfolio management tasks involving work item classification, mix analysis, SLA aging, release readiness, blockers, and dependencies. Use when the task asks you to interact with a shared portfolio REST API at a TASK_ENV_BASE_URL, classify work items into NewFeature/TechDebt/Reliability/Security categories, compute portfolio mix gaps, assess SLA breach rates, evaluate release readiness, or produce structured JSON answers following an answer template. Covers mix-target comparison, duplicate/cancelled/mirror-stale record detection, blocker cause analysis, and dependency chain tracing.

experiments/codex_skill_creator_comparison_deepseek_v4_pro_max/reports/skills/task_group_024/fewshot/codex/fewshot_attempt_03/SKILL.md

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Repository stars (not skill ratings): 121
Repository last updated: Oct 29, 2026
License: Apache-2.0

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self-evolving Repository topic
self-learning Repository topic
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SKILL.mdcore · 5,809 bytes
SKILL.mdcore · 5,809 bytes
agents/openai.yamlasset · 220 bytes
references/category_rules.mddoc · 2,657 bytes
references/data_quality.mddoc · 3,204 bytes
references/portfolio_api.mddoc · 6,580 bytes
scripts/query_portfolio.pyruns · 2,738 bytes

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# Portfolio Management

Solve portfolio management tasks in a shared test environment. The environment exposes work items, mix targets, SLA policy, releases, milestones, blockers, and dependencies through REST endpoints and a read-only SQL query endpoint.

## Workflow

1. Read `environment_access.md` in the workspace for the base URL, allowed endpoints, and any required auth tokens.
2. Fetch reference data from the REST endpoints: work-items, mix-targets, sla-policy, releases, milestones, dependencies, blockers.
3. Use [POST /api/query](references/portfolio_api.md) (SQL) for filtered work-item queries when REST pagination or filtering is insufficient.
4. Classify work items using [category rules](references/category_rules.md).
5. Distinguish primary, duplicate, cancelled, and mirror-stale records using [data quality rules](references/data_quality.md).
6. Compute metrics with correct precision: percentages to 1 decimal place, rates to 3 decimal places.
7. Follow the answer template schema exactly. Produce valid JSON only.