Run a daily Amazon account-health check: Account Health Rating (AHR), order-defect rate, late-shipment rate, valid-tracking rate, cancellation rate and policy violations - each scored against Amazon's own target and rolled up to a single red / amber / green verdict with the exact issues to fix first. Live from DataDoe, in chat, no dashboard. Use when the user asks about "account health", "is my account ok", "AHR", "account health rating", "am I at risk of suspension", "order defect rate", "late shipment rate", "policy violations", or a "daily account check".
The full skill specification, rendered straight from the source repository.
Daily Amazon Account Health Check
A daily smoke alarm for your Amazon account. It reads your live account-health
metrics from DataDoe, compares each one to Amazon's own target, and gives you a
single red / amber / green verdict plus the exact issues to fix first. Runs
entirely in chat through the DataDoe MCP - no dashboard to build, no report to
download.
When to use this
Every morning, as the first thing you check ("how is my account today").
Right after Amazon emails you about a policy or performance issue.
Before you launch a big promotion or send inventory in, to be sure the account
is in good standing.
Trigger phrases: "account health", "is my account ok", "AHR", "account health
rating", "am I at risk of suspension", "order defect rate", "late shipment
rate", "policy violations".
The framework. The Five Health Gates
Amazon can restrict selling for different reasons, so check them in order of how
fast they can hurt you:
Account Health Rating (AHR) - the master score (Amazon's AHR runs 0-1000;
= 200 is healthy). Prefer the _status field (e.g. GREAT / GOOD / AT_RISK /
CRITICAL) - green if healthy, amber if at-risk, red if critical - and fall back
to the score vs 200 only if status is missing.
Policy compliance - listing policy violations, suspected/received IP
complaints, product authenticity/condition/safety complaints, restricted
product violations (target for each is 0).
Open warnings - the count of active policy warnings that need action.
A single red gate outranks five green ones. Report the worst gate first.
Configuration
MCP base: https://mcp.datadoe.com/mcp/v1
Data source: Seller Account Health Metrics (table amazon_seller_performance). One row per marketplace per day; the latest
date is the current state.
Currency/marketplace: read marketplace_country_code; localise language and
currency to it.
Step-by-step workflow (MCP-native)
sellers_and_vendors_list -> pick the seller. Keep its id as
sellerOrVendorId.
exports_sources_get with a query like "seller account health" to confirm
source amazon_seller_performance is enabled for this org. If disabled, tell the user to
enable it in Settings > Data and stop.
exports_create for source amazon_seller_performance, this seller, most recent day. Ask
for these columns:
the *_6m_count policy-violation columns (listing policy, suspected IP, received IP, product authenticity/condition/safety, restricted product, other)
seller_policy_violations_6m_warning_count
Poll until the export is ready, then exports_raw_download (or
exports_raw_url_get) and read the single latest row.
Score each gate against its target using the *_status field where present,
otherwise compare *_value to *_target_less_than / *_target_greater_than.
Roll up to one overall verdict (worst gate wins) and render the output card.
Output format
text
1Account Health - {marketplace} - {date}
2Overall: {GREEN | AMBER | RED} AHR {score}
34Gate Metric Value Target Status
5Master Account Health Rating {score} >= 200 {G/A/R}
6Customer Order Defect Rate {v}% < 1% {G/A/R}
7Customer Late Shipment Rate {v}% < 4% {G/A/R}
8Customer Cancellation Rate {v}% < 2.5% {G/A/R}
9Delivery Valid Tracking Rate {v}% > 95% {G/A/R}
10Delivery On-Time Delivery Rate {v}% > 90% {G/A/R}
11Policy Open violations (6m) {n} 0 {G/A/R}
12Policy Active warnings {n} 0 {G/A/R}
1314Fix first:
151. {worst gate, plain-English action}
162. {next}
17Nothing urgent today. -> only if every gate is green.
Keep it scannable. Lead with the overall verdict, then the single most important
action. Do not paste every column.
Worked example
AHR 245 (green). Order Defect Rate 0.4% vs < 1% (green). Late Shipment Rate 6.1%
vs < 4% (red). Valid Tracking 97% (green). 1 listing-policy violation (red).
Overall: RED (a red gate outranks the greens).
Fix first: (1) Late Shipment Rate is 6.1%, above Amazon's 4% ceiling - check
carriers and handling time on recent orders. (2) Resolve the 1 open listing
policy violation in Account Health before it compounds.
Quality self-check
Did I use the latest date row only (not sum multiple days)?
Did I compare each metric to its own target column, not a hard-coded number?
Is the currency/units correct for this marketplace?
Did I lead with the worst gate and give a concrete next step, not a data dump?
Common mistakes
Averaging metrics across days. Account health is a snapshot - use MAX(date).
Treating a green AHR as "all fine" while a policy violation is open.
Reporting raw numbers with no target context (2% ODR means nothing without the
< 1% target).
Hard-coding targets. Amazon can change them; the *_target_* columns are canon.
Notes
Read-only. This skill never writes to the account.
A DataDoe skill, built on the DataDoe amazon_seller_performance source.