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.
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.
npx agentmods add skills/microsoft/dataverse-business-skills/competitive-intelligencenpx skills add microsoft/dataverse-business-skills --skill competitive-intelligencegit clone --depth 1 https://github.com/microsoft/dataverse-business-skillsWrote 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.
[](https://agentmods.dev/skills/microsoft/dataverse-business-skills/competitive-intelligence)<a href="https://agentmods.dev/skills/microsoft/dataverse-business-skills/competitive-intelligence"><img src="https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/competitive-intelligence.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00085 | $0.04199 |
| Opus 5 | $0.00043 | $0.02099 |
| Sonnet 5 | $0.00017 | $0.00840 |
| Haiku 4.5 | $0.00009 | $0.00420 |
Grade A, and why
competitive-intelligence 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 454 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Intelligence
Competitive insights are often locked in deal notes, lost opportunity records, and anecdotal rep knowledge. This skill mines Dataverse to surface structured competitive intelligence: which competitors appear most frequently, where deals are being lost to them, what deal patterns correlate with wins vs losses, and what talking points reps should use. This is the Dataverse-internal equivalent of competitive research — drawing from closed deal history rather than external sources.
Instructions
Step 1: Identify Competitor or Analysis Scope
Accept input from the user:
- Specific competitor name (to analyze one rival)
- All competitors (for a full competitive landscape view)
- Time range (default: last 12 months)
- Segment filter (by owner, territory, deal size, or industry)
Calculate date range for analysis: createdon >= '[start_date]'
Step 2: Identify Lost Deals with Competitor Information
Important: The opportunity entity does not have a direct competitorid field — the opportunity-to-competitor relationship is many-to-many (opportunitycompetitors_association). When an opportunity is closed, Dynamics 365 creates an opportunityclose activity record which does have a direct competitorid lookup. Use opportunityclose for structured competitor data on closed deals.
Query closed-lost opportunityclose records:
SELECT oc.opportunityid, oc.competitorid, oc.description, oc.createdon,
oc.actualrevenue
FROM opportunityclose oc
WHERE oc.statecode = 1
AND oc.createdon >= '[start_date]'
ORDER BY oc.createdon DESC
Then join to the opportunity table by opportunityid to get deal details:
SELECT opportunityid, name, estimatedvalue, actualclosedate, salesstage,
description, ownerid, customerid, closeprobability
FROM opportunity
WHERE statecode = 2
AND actualclosedate >= '[start_date]'
ORDER BY actualclosedate DESC
Note: If opportunityclose is not populated (competitor not selected at close), fall back to text pattern matching in opportunity description fields as described in Step 3.
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.
- 6d ago First seen · 454 lines · 85 tokens per session scan A 3ef10ea6b41d
competitive-intelligence is a skill published in the GitHub repository microsoft/dataverse-business-skills (49 stars, last pushed 5mo ago), licensed MIT. It adds 85 tokens to every session and 4,199 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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