account-risk-early-warning

account-risk-early-warning is a skill for Claude Code, Codex from microsoft/dataverse-business-skills. It costs 80 tokens per session (4,843 once invoked), scanned A, original, MIT.

An account-monitoring helper that looks for signs a customer may stop using or buying from a company.

In plain words
What is it for?
Finding at-risk accounts, checking customer health, ranking churn risk, and deciding which customers need attention first.
Why use it?
It brings together activity, support cases, and engagement changes so teams can spot customer problems before they become lost accounts.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Finding at-risk accounts, checking customer health, ranking churn risk, and deciding which customers need attention first.

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Install with agentmods
npx agentmods add skills/microsoft/dataverse-business-skills/account-risk-early-warning
About the project

Dataverse Business Skills is a collection of natural-language instructions that teach AI agents how to follow business processes, policies, and domain knowledge for Microsoft Dataverse. Organizations use the skills with Dataverse environments connected to products such as Power Apps, Dynamics 365, or Power Platform. The catalogue entries are skills from this collection.

microsoft/dataverse-business-skills · 50 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add microsoft/dataverse-business-skills --skill account-risk-early-warning
Clone the repo
git clone --depth 1 https://github.com/microsoft/dataverse-business-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for account-risk-early-warning

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/account-risk-early-warning/github.svg)](https://agentmods.dev/skills/microsoft/dataverse-business-skills/account-risk-early-warning)
Your own site
<a href="https://agentmods.dev/skills/microsoft/dataverse-business-skills/account-risk-early-warning"><img src="https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/account-risk-early-warning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for account-risk-early-warning

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/dataverse-business-skills/account-risk-early-warning"><img src="https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/account-risk-early-warning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,843 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.04843
Opus 5 $0.00040 $0.02422
Sonnet 5 $0.00016 $0.00969
Haiku 4.5 $0.00008 $0.00484

Measured 12d ago against content hash 5be6e2357f3f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

account-risk-early-warning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/account-risk-early-warning/SKILL.md · 545 lines

How it starts

The opening of the file, as written. The whole thing — 545 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Account Risk Early Warning

Retaining existing customers is more cost-effective than acquiring new ones. This skill monitors key accounts for early warning signals that indicate potential churn or relationship issues, enabling proactive intervention before problems escalate.

Instructions

Step 1: Determine Scope

When user asks "Which of my top accounts are showing warning signs?":

1.1 Define Account Set:

Options:
A) All active accounts owned by user
B) Specific account list (e.g., enterprise tier)
C) Accounts with revenue above threshold
D) Accounts up for renewal in next X months

1.2 Query Target Accounts:

SELECT accountid, name, revenue, numberofemployees, industrycode,
       createdon, ownerid, customertypecode, territoryid,
       openrevenue, openrevenue_date
FROM account
-- Note: openrevenue and openrevenue_date are rollup fields that may not exist in all orgs.
-- If absent, calculate open pipeline value by querying the opportunity table directly.
WHERE statecode = 0
AND ownerid = '[current_user_id]'  -- or specific criteria
ORDER BY revenue DESC
Step 2: Analyze Risk Signals for Each Account

Important: Dataverse SQL Limitations Dataverse SQL does NOT support: subqueries, DATEADD(), GETUTCDATE(), HAVING, DISTINCT, UNION, CASE statements. Use separate queries and calculate date filters programmatically (e.g., calculate '2025-09-01' for 6 months ago).

2.1 Activity Trend Analysis Query recent activities for each account (run separately per account):

SELECT activityid, activitytypecode, createdon, statecode
FROM activitypointer
WHERE regardingobjectid = '[accountid]'
AND createdon > '2025-09-01'
ORDER BY createdon DESC

Calculate Activity Metrics:

For each account:
- Total activities (last 6 months)
- Activities per month trend
- Activity types breakdown
- Days since last activity
- Comparison to account's historical average

Activity Risk Indicators:

Signal Warning Critical
Days Since Last Activity 30+ days 60+ days
Month-over-Month Decline 25%+ decline 50%+ decline
No Meetings/Calls 45+ days 90+ days
Only Automated Emails 30+ days 60+ days

Read the full file on GitHub · 545 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 545 lines · 80 tokens per session scan A 5be6e2357f3f

Subscribe to this mod's changes

account-risk-early-warning is a skill published in the GitHub repository microsoft/dataverse-business-skills (50 stars, last pushed 6mo ago), licensed MIT. It adds 80 tokens to every session and 4,843 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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