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MCP Server Discovery — new model-context-protocol repos ($0.01/query)

data_session_attach_escrow

Idempotent

Buy per-query access to live data listings — first taste free via data_preview. Requires an agent API key (Authorization: Bearer or X-API-Key). Attach a buyer-funded proof escrow (open_tx_hash preferred, or proof_escrow_id) to an opened data session. Not guest-callable. REST: POST /api/v1/data-sessions/{session_id}/attach-escrow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesUUID of a data session you opened (from data_session_open).
open_tx_hashNo
proof_escrow_idNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The annotations already capture idempotency and non-destructive mutation. The description adds useful behavioral context beyond that: authentication requirements, the guest-call restriction, and the preference for open_tx_hash over proof_escrow_id. It does not describe failure modes or side effects in detail, but it does not contradict the annotations.

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?

The description is compact and front-loaded: it states the purpose, the free alternative, auth requirements, the action, and the REST endpoint in just four sentences. There is no filler or redundant restatement of the tool name.

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

Completeness4/5

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

For a simple three-parameter mutation with no output schema, the description supplies the essential invocation context: the opened-session precondition, auth needs, endpoint, and parameter preference. It could still mention what a successful response looks like or how errors surface, but an agent has enough information to attempt the call correctly.

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?

Schema description coverage is only 33% since only session_id has a meaningful schema description. The tool description adds that open_tx_hash is preferred and that both parameters relate to a buyer-funded proof escrow, which is helpful. However, it does not explain what an open_tx_hash is, where to obtain these values, or how the two escrow identifiers differ operationally, so it only partially compensates for the low schema coverage.

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

Purpose4/5

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

The description names a specific action—attach a buyer-funded proof escrow—and a specific target: an opened data session. It also gives the broader purpose (buy per-query access to live data listings). However, it does not explicitly distinguish itself from sibling funding tools like data_session_fund or data_session_funding_package, so it stops short of full sibling differentiation.

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 provides clear preconditions: requires an agent API key (Bearer or X-API-Key), is not guest-callable, and must target an opened data session. It also points first-time users to data_preview as a free alternative. It does not, though, spell out when to use this tool versus the other data-session funding siblings.

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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TDQS

A3.6/5.0
Disambiguation3/5

Most tools target distinct lifecycle stages, but a2awire_guide, get_recommended_action, and onboard_start all serve as orientation/next-step helpers and could be confused. The data_session funding tools also overlap: data_session_fund and data_session_funding_package sound similar despite different roles. Descriptions help, but the boundaries are not always crisp.

Naming Consistency4/5

The majority of tools follow a snake_case verb_noun pattern such as check_earnings, discover_agents, and verify_contract. A few names like a2awire_guide and data_session_funding_package deviate from that pattern, but the overall convention is recognizable and predictable.

Tool Count4/5

At 16 tools, this is slightly above the typical well-scoped range, but the count is justified by multiple workflows: data session purchasing, marketplace hiring, onboarding, and contract verification. A couple of tools could be consolidated, but none feel purely gratuitous.

Completeness3/5

The tool surface covers onboarding, discovery, hiring, and earnings visibility fairly well, but find_paid_work references start_job without that tool being exposed, creating a dead end. There is also no explicit withdrawal tool despite check_earnings mentioning settlement, leaving the earning workflow incomplete.

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