Individual skill
asteria-fleet-dq-audit
Audit, reconcile, and certify an Asteria Fleet Data Quality Hub collection (fuel, freight, maintenance, or contacts family) against a case scope, then return ONE JSON object that conforms exactly to a supplied answer_template.json. Use when a task points at the Asteria Fleet Data Quality Hub at <TASK_ENV_BASE_URL>, stages payloads/case_scope.json + payloads/answer_template.json, and asks for a reconciliation / canonicalization / certification / close decision as strict JSON. Covers source-snapshot reconciliation, duplicate resolution, category/class mismatch + quarantine classification, unit + FX normalization, focus rollups, exception rankings, opaque Asteria control-code inference, and threshold-based certification status.
experiments/claude_code_glm_5_2_max/reports/skills/task_group_021/self/self_attempt_03/SKILL.md
Source commit 5082a777379156a048881e94940d640702e5e09a
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- Last checked
- Nov 6, 2026
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- Repository last updated
- Oct 29, 2026
- License
- Apache-2.0
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- agent Repository topic
- ai Repository topic
- benchmark Repository topic
- llm Repository topic
- self-evolving Repository topic
- self-learning Repository topic
- skills Repository topic
- data Derived category
- security Derived category
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# Asteria Fleet Data Quality Hub — audit & certification
This skill executes a single, repeatable operating procedure distilled from five audit task
families (fuel, freight, maintenance, partner-onboarding contacts, field-service-roster contacts).
It produces **one JSON object** that conforms exactly to the task's `answer_template.json`.
The procedure is family-agnostic. The case scope and answer template are always the source of truth
for *what* to compute and *how* to shape the output; this skill supplies the *how to operate the hub*
and the *cross-cutting reconciliation rules*. Per-family specifics live in
`references/family_playbooks.md`; the hub API contract in `references/hub_api.md`; opaque control-code
inference in `references/control_codes.md`.
## 0. Contamination guard (run first)