Microsoft Windows Security Updates (MSRC CVRF) — buy per-query in-session (msrcwatch)

data_session_open

Buy per-query access to live data listings - first taste free via data_preview. Listing: msrcwatch: Microsoft MSRC Security Updates (0.01 USDC/query (max 20 queries/session)). Open a prepaid session, then fund and query.

Input Schema

TableJSON Schema

Name	Required	Description
`listing_id`	No	UUID of the listing. Provide exactly one of listing_slug or listing_id.
`max_queries`	No
`listing_slug`	No	Public listing slug (from benchmarks_get / data_directory_get). Provide exactly one of listing_slug or listing_id.
`open_tx_hash`	No
`buyer_address`	No	Buyer EVM address. Optional: defaults to your own platform wallet when omitted.
`proof_escrow_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed13 schema fields changedSep 7, 2026

addedInput schema / description

Added value: +"MCP-only input for ``data_session_open``.\n\nSubclasses the REST ``DataSessionOpen`` payload without mutating it (the\n``FaucetUsdcDripInput`` approach) so the shared constraints\n(``max_queries`` bounds, ``open_tx_hash`` length, the EVM address check)\nstay declared once. Two friction-free relaxations, MCP surface only:\n\n* the listing may be named by its public slug OR its UUID (exactly one) -\n  the benchmark route and the purchase-gate 409 hand the agent a slug, and\n  demanding a UUID re-creates the slug-to-UUID lookup hop;\n* ``buyer_address`` is optional - when omitted the handler defaults to the\n  caller's own platform wallet (``WalletService.own_wallet_address``),\n  the same argument-filling default the USDC faucet uses.\n\nThe REST endpoint ``POST /api/v1/data-sessions`` keeps requiring\n``listing_id`` + ``buyer_address`` unchanged.\n\nThe ``type: ignore[assignment]`` marks are the intended pydantic override\n(narrowing the REST fields to Optional here); mypy reads that as an LSP\nviolation even though the model validator enforces exactly one listing\nreference and the handler guards the Optionals."

addedInput schema / properties / buyer_address / anyOf

Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / properties / buyer_address / default
```
Added value: +null
```

addedInput schema / properties / buyer_address / description

Added value: +"Buyer EVM address. Optional: defaults to your own platform wallet when omitted."

removedInput schema / properties / buyer_address / type
```
Removed value: -"string"
```

addedInput schema / properties / listing_id / anyOf

Added value: +[
+  {
+    "format": "uuid",
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / properties / listing_id / default
```
Added value: +null
```

addedInput schema / properties / listing_id / description

Added value: +"UUID of the listing. Provide exactly one of listing_slug or listing_id."

removedInput schema / properties / listing_id / format
```
Removed value: -"uuid"
```
removedInput schema / properties / listing_id / type
```
Removed value: -"string"
```

addedInput schema / properties / listing_slug

Added value: +{
+  "anyOf": [
+    {
+      "minLength": 1,
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Public listing slug (from benchmarks_get / data_directory_get). Provide exactly one of listing_slug or listing_id.",
+  "title": "Listing Slug"
+}

removedInput schema / required

Removed value: -[
-  "listing_id",
-  "buyer_address"
-]

changedInput schema / title

Previous value: -"DataSessionOpen"New value: +"DataSessionOpenInput"

First observedSep 7, 2026

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are all false, so they contribute little; the description adds cost (0.01 USDC/query), prepaid nature, and a 20-query session cap. It doesn't disclose return values, wallet/auth requirements, or other side-effect details, so it is useful but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with the core action and workflow front-loaded. Each sentence earns its place: free alternative, pricing/quota context, and the open-then-fund-then-query sequence. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The input schema's property and top-level descriptions carry the parameter constraints (exactly one listing reference, optional buyer_address), and the tool description supplies workflow and pricing. The lack of an output schema or return-value description is a real gap, but the tool is simple enough that an agent can likely chain it with data_session_fund and data_session_query.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds real-world semantics for max_queries (20-query session cap) and listing_slug (msrcwatch), going beyond bare schema bounds. It doesn't explain open_tx_hash or proof_escrow_id, though the schema's property descriptions already cover listing_id/slug and buyer_address.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific action (open a prepaid data session) and resource (live data listings), and the phrase 'first taste free via data_preview' distinguishes it from the free preview sibling. The concrete msrcwatch example reinforces the listing concept without obscuring the general purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tells the agent to use data_preview for the free first taste and lays out the order: open, then fund, then query, which maps naturally to data_session_fund and data_session_query. It doesn't explicitly name those siblings or give when-not-to-use conditions, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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