Science News Tracker — latest research & discovery headlines (scinews)

data_session_open

Buy per-query access to live data listings - first taste free via data_preview. Listing: scinews: Latest science news & breakthrough headlines (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. Dates show when Glama detected each change.

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 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds that opening a session is a prepaid action and requires a later funding step, but it does not explain side effects such as creating a session record or initiating a blockchain transaction. It also does not clarify failure modes or the cost implications of opening a session.

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

Conciseness2/5

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

The description is overlong and includes technical implementation rationale (type: ignore marks, mypy LSP violation, REST endpoint behavior) that is irrelevant to an AI agent selecting or invoking the tool. The marketing-style opening and the technical digression could be condensed to a clear purpose statement plus parameter guidance. The structure mixes promotional language with developer notes, making it less scannable.

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 description gives enough context to understand that opening a session is the first step before funding and querying, but it does not explicitly name the sibling tools (data_session_fund, data_session_query) or explain the overall workflow. It also provides no information about the return value or output of the tool, which is especially important given the absence of an output schema.

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 schema covers 50% of parameters. The description adds valuable semantics for listing_id/listing_slug (exactly one required) and buyer_address (defaults to own wallet), and it explains why these relaxations exist. However, max_queries, open_tx_hash, and proof_escrow_id have no user-facing explanation, and the description spends space on internal implementation details (pydantic overrides, mypy) rather than providing parameter guidance.

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?

The description clearly states the tool's purpose: buying per-query access to live data listings and opening a prepaid session for subsequent funding and querying. It distinguishes itself from the free data_preview alternative and implies its role relative to the fund and query sibling tools.

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?

The description implies when to use this tool ('Open a prepaid session, then fund and query') and explicitly points to data_preview for a free first look. It also gives precise guidance on selecting a listing via slug or UUID. However, it does not explicitly state when not to use it or how it relates to the data_session_fund and data_session_query sibling tools beyond the sequential implication.

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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