purview-dlp-integration

purview-dlp-integration is a skill for Claude Code from microsoft/agent365-skills. It costs 200 tokens per session (6,679 once invoked), scanned A, original, MIT.

An integration that adds Microsoft Purview data-loss prevention checks to an existing Microsoft Agent 365 agent. It checks prompts through Microsoft Graph, blocks inputs containing data covered by a policy, and can audit responses.

In plain words
What is it for?
It is for adding prompt blocking and response auditing to Node.js, Python, or .NET agents using Microsoft Purview.
Why use it?
It helps stop sensitive information such as credit-card numbers, Social Security numbers, or other personal data from reaching the AI model, while recording response checks for review.

Skill for Claude Code ✓ vendor

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; names the AskUserQuestion tool; mentions Claude Code.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the agent365 plugin — 8 skills shipped together

Good fit It is for adding prompt blocking and response auditing to Node.js, Python, or .NET agents using Microsoft Purview.

Compare 6 skills from other repositories ↓
About the project

Microsoft Agent 365 Skills is a collection of coding-agent skills and MCP configuration for building and operating AI Teammates hosted in Microsoft Teams. It supports the Agent 365 lifecycle, including WorkIQ integration, registration, observability, validation, and local testing, for users of Claude Code and GitHub Copilot.

microsoft/agent365-skills · 51 stars · on GitHub

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add microsoft/agent365-skills
Claude Code
/plugin install agent365

Made for: Claude Code.

Or install agent365, the plugin that ships this one along with the rest of its 8 skills.

Wrote this? Show the measurements

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README.md
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Your own site · 80×15
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Per session 200 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,679 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 $0.00200 $0.06679
Opus 5.5 $0.00080 $0.02672
Sonnet 5.5 $0.00040 $0.01336
Haiku 4.5 $0.00020 $0.00668

Measured 1mo ago against content hash 4fdcb1e11fdd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

purview-dlp-integration 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 1mo ago.

The scan reads SKILL.md. This mod also ships 8 executable files (assets/purview-s2s.ts, assets/purview.py, assets/purview.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/agent365/skills/purview-dlp-integration/SKILL.md · 386 lines

How it starts

The opening of the file, as written. The whole thing — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Microsoft Purview DLP Integration for Agent 365

Trigger phrases — any of these will activate this skill automatically:

  • "add Purview DLP to my agent"
  • "add data loss prevention to my A365 agent"
  • "block credit cards / SSNs / PII before my agent's LLM sees them"
  • "enforce compliance / audit on agent prompts and responses"
  • "wire a DLP gate into my agent code"
  • "call the Graph processContent API from my agent"
  • "add Purview blocking to my Node.js / Python / .NET agent"

Add a Purview data-loss-prevention gate before an existing A365 agent's LLM call: each prompt is evaluated via the Graph processContent API and blocked when an input-blocking policy matches. Optional response checks provide audit, not response blocking, for the supplied Applications policy. processContent sends the checked text to Microsoft Purview for evaluation and audit. Designed for minimal, reversible changes to the customer's agent.

When to use

  • "Add Purview DLP / data loss prevention to my agent."
  • "Block credit cards / SSNs / PII before my agent's LLM sees them."
  • "Enforce compliance / audit on agent prompts and responses."
  • Any A365 agent — Node.js, Python, or .NET — that needs inline DLP.

When NOT to use

  • Adding OpenTelemetry tracing / MAC Activity telemetry → use instrument-observability.
  • Diagnosing why telemetry isn't reaching MAC Activity / Defender → use a365-code-validator.
  • Provisioning the blueprint / Entra permissions from scratch → use a365-setup / make-a365-agent first, then return here.

How it works

user turn ─► [INPUT gate] processContent(uploadText, /me)  ─► block? ─► reply "blocked", STOP (LLM never called)
                                                            └─ allow ─► LLM ─► optional output audit ─► reply
  • Token: the agent's agentic delegated Graph token, evaluated as /me (the agent identity) — acquired via the agent's own auth handler: Node.js GetAgenticUserToken, Python authorization.exchange_token(…), .NET UserAuthorization.GetTurnTokenAsync(…). A365 blueprint apps cannot use app-only client-credentials here — Graph strips data-plane roles from that token.
  • Fail-closed by default: any Purview error/timeout blocks the turn.
  • Content limit: delegated guards reject messages over 100,000 characters before sending them to Graph, even in fail-open mode. They never approve a full message based on a prefix.
  • Output: PURVIEW_CHECK_OUTPUT=true submits responses for audit. The supplied workload does not support DownloadText blocking; do not promise that it filters sensitive responses. With fail-closed mode, a failed output audit still withholds the reply.
  • Policy: a dedicated Purview DLP policy scoped to the agent's Entra app id (portal: "Managed cloud apps" / Applications workload) with a RestrictAccess=Block rule.

Read the full file on GitHub · 386 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. 1mo ago First seen · 386 lines · 200 tokens per session scan A 4fdcb1e11fdd

Subscribe to this mod's changes

purview-dlp-integration is a skill published in the GitHub repository microsoft/agent365-skills (51 stars, last pushed 17d ago), licensed MIT. It adds 200 tokens to every session and 6,679 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-16.

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