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Trending Repository Tracker — new GitHub repo discovery ($0.01/query)

data_session_open

Buy per-query access to live data listings — first taste free via data_preview. Listing: ghtrend: fast-growing new GitHub repositories (0.01 USDC/query (max 20 queries/session)). Open a prepaid session, then fund and query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listing_idYes
max_queriesNo
open_tx_hashNo
buyer_addressYes
proof_escrow_idNo

Schema Changelog

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

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

The annotations only signal non-read-only behavior, so the description adds useful behavioral context: the session is prepaid, per-query priced, and capped at 20 queries per session. It does not disclose whether a wallet transaction is required, what the return value is, or the consequences of opening an unfunded session, making this partial rather than complete.

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

Conciseness4/5

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

Two sentences front-load the core purpose and pricing, then give the workflow. The listing-specific example is useful but slightly narrows what is otherwise a general tool description.

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

Completeness2/5

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

With five parameters, no output schema, and no per-parameter documentation, the description is too sparse for an agent to safely construct a valid call. It lacks input formats, expected return values, and the dependency relationship with funding/escrow steps, so the workflow narrative alone is not enough.

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

Parameters2/5

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

Schema description coverage is 0%, and the description never names listing_id, buyer_address, max_queries, open_tx_hash, or proof_escrow_id. The mention of 'ghtrend' and 'max 20 queries/session' gives hints about listing_id and max_queries, but the required buyer_address and the transaction/escrow parameters remain unexplained.

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 identifies a concrete action ('open a prepaid session') and a concrete resource ('data listings', specifically the ghtrend listing), so an agent can tell what the tool does. It doesn't sharply differentiate from sibling session tools like data_session_fund or data_session_query beyond the workflow sequence, which keeps it from a 5.

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?

It explicitly points to data_preview as the free first step and places this tool in a clear sequence: open a session, then fund and query. It doesn't discuss when to prefer data_session_attach_escrow or data_session_funding_package, so the guidance is context-rich but not exhaustive.

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

B3.3/5.0
Disambiguation2/5

Several tools cluster around the same actions: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe paying for session access; a2awire_guide and get_recommended_action both tell the agent what to do next; discover_agents and hire_and_execute both search by capability. Only a few tools like data_preview, check_earnings, and verify_contract are cleanly distinct.

Naming Consistency2/5

All names use snake_case, but there is no consistent verb_noun or action pattern: data_preview and a2awire_guide are nouns, data_session_open is object+verb, data_session_funding_package is object+gerund+noun, and hire_and_execute is verb+verb. The fund/funding_package pair is especially confusing.

Tool Count2/5

16 tools is heavy for a server whose stated purpose is a single repo-trend data listing, and most tools are unrelated A2AWire marketplace, onboarding, and escrow operations. The data-access path could be served by 4-5 tools, so the extra redundant payment and meta-navigation tools make the set over-sized.

Completeness2/5

The GitHub data query path (preview -> open -> fund -> query) is mostly covered, but the broader exposed surface has a clear dead end: find_paid_work instructs callers to call start_job, yet no start_job tool exists. There is also no way to manage sessions or agents beyond basic onboarding, so agents following the provided recommendations can fail.

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