competitive-intelligence

competitive-intelligence is a skill for Claude Code, Codex from microsoft/dataverse-business-skills. It costs 85 tokens per session (4,199 once invoked), scanned A, original, MIT.

A tool for analyzing past sales opportunities in Microsoft Dataverse, a business database used by Dynamics 365. It compares results involving competitors and identifies recurring patterns.

In plain words
What is it for?
Use it to compare win and loss rates, study one competitor or the full competitive landscape, and prepare talking points for sales representatives.
Why use it?
Competitive knowledge is often scattered across deal notes and lost-opportunity records. This organizes that history so teams can see where they win or lose.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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 · 49 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.

agentmods
npx agentmods add skills/microsoft/dataverse-business-skills/competitive-intelligence
Any agent
npx skills add microsoft/dataverse-business-skills --skill competitive-intelligence
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 competitive-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/competitive-intelligence.svg)](https://agentmods.dev/skills/microsoft/dataverse-business-skills/competitive-intelligence)
Your own site
<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>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,199 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00085 $0.04199
Opus 5 $0.00043 $0.02099
Sonnet 5 $0.00017 $0.00840
Haiku 4.5 $0.00009 $0.00420

Measured 6d ago against content hash 3ef10ea6b41d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

skills/competitive-intelligence/SKILL.md · 454 lines

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.

Read the full file on GitHub · 454 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. 6d ago First seen · 454 lines · 85 tokens per session scan A 3ef10ea6b41d

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens