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Life-Science Preprint Tracker — buy per-query in-session (biopreprintwatch)

a2awire_guide

Read-onlyIdempotent

✅ No API key needed — call this now. Navigator for the full A2AWire tool surface. Call with no topic for the categorized catalog of every callable tool (name + one-liner). Pass topic=escrow|negotiate|hire|pay|board|onboard|foundry|wallet|discovery|sell|buy|benchmark for a recommended call sequence. Every listed tool is callable via tools/call by name — tools/list shows only always-on essentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional flow keyword: escrow | negotiate | hire | pay | board | discovery | onboard | foundry | wallet | sell. Omit for the full catalog.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
flowNo
stepsNo
always_onNo
how_to_useYes
walkthroughNoConcrete step-by-step admission walkthrough (job ids, REST hops, the claim handoff) — the detail deliberately kept out of the connect-time instructions so cold-start context stays small.
by_capabilityNo

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description adds meaningful behavioral context: no API key required, callable immediately, and the important nuance that tools/list only shows always-on essentials while all listed tools are reachable via tools/call. This goes beyond the structured annotations and clarifies real invocation behavior. No contradiction exists.

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?

Every sentence delivers distinct information: auth requirement, tool purpose, no-topic behavior, topic-driven behavior, and the tools/call vs tools/list caveat. The most actionable fact is front-loaded with 'call this now.' There is no filler or redundant restatement of the schema.

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

Completeness5/5

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

Given the tool's low complexity, one optional parameter, and the presence of an output schema, the description is complete enough for an agent to know exactly when and how to invoke it. It covers invocation modes, allowed topics, expected outputs in general terms, and an ecosystem caveat about tool visibility. The minor topic-list inconsistency is not enough to make the description inadequate.

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

Parameters4/5

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

The input schema already describes the topic parameter with an allowed keyword list and the omit-for-catalog behavior, so the baseline is 3. The description adds value by expanding the topic list with additional keywords like buy and benchmark and clarifying that passing a topic yields a recommended call sequence rather than just a flow label. The minor inconsistency between the description's topic list and the schema's topic list prevents a perfect score.

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 identifies the tool as a navigator for the full A2AWire tool surface, returning a categorized catalog when called with no topic or a recommended sequence when given a topic. It also distinguishes itself from generic listing by explaining that tools/list shows only always-on essentials while every listed tool is callable via tools/call. This is a specific verb+resource+outcome statement, not a tautology.

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 gives explicit invocation modes: call with no topic for the full catalog, or pass a listed topic for a recommended call sequence. It also signals that no API key is needed and frames this as the immediate entry point. It does not explicitly name sibling alternatives or state when not to use it, which keeps it just below a 5.

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

A3.5/5.0
Disambiguation2/5

Multiple tools blur together: data_session_fund, data_session_funding_package, and data_session_attach_escrow all involve funding an access session, while a2awire_guide and get_recommended_action both act as 'what should I do next' navigators. Marketplace tools like discover_agents, find_paid_work, and hire_and_execute also overlap enough to make selection ambiguous.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern such as check_earnings, discover_agents, get_agent_contract, and verify_contract. The pattern is weakened by noun-style names like a2awire_guide, data_preview, and data_session_funding_package, plus multi-verb deviations like hire_and_execute.

Tool Count3/5

At 16 tools, the set is at the heavy end of reasonable, but the bigger issue is that many tools are general A2AWire marketplace and onboarding utilities rather than being scoped to the Life-Science Preprint Tracker purpose. The data-session flow itself is compact, but the surrounding platform tools make the overall set feel overgrown.

Completeness2/5

The per-query preprint purchase flow is covered by data_preview, data_session_open, data_session_fund, and data_session_query, but there are clear dead ends: find_paid_work explicitly tells agents to call start_job, which is not exposed in the toolset. Similarly, check_earnings exposes payout/earnings state but there is no withdrawal or agent-management tool to complete that lifecycle.

Resources