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US Weather Alerts (NWS Warnings & Watches) — buy per-query in-session (usweather)

data_preview

Read-onlyIdempotent

✅ No API key needed — call this now. Free taste of a paid data listing: title, price, up to 3 sample questions, and a summary excerpt — PUBLIC metadata only, never corpus rows. Defaults to the routed session's listing (or pass slug). Optional question (≤300 chars) is echoed back. Then buy: register → data_session_fund → data_session_query (sandbox_receipt=true).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoPublic listing slug. Defaults to the routed session's listing when connected via /mcp/data/{slug}/http.
questionNoOptional free-text question you'd ask this data (echoed back).

TDQS

A5/5.0
Behavior5/5

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

While annotations already mark this read-only/idempotent/non-destructive, the description adds concrete behavioral facts: public metadata only, never corpus rows, optional question echoed back, and the default routed-session listing behavior. It also discloses the access context (no API key) and frames the output scope beyond what annotations alone provide.

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 dense but every clause earns its place: access signal, output fields, data boundary, routing default, parameter behavior, and buy path. The flow is front-loaded and visually structured with arrows, making the decision sequence easy to extract.

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?

For a two-optional-parameter read-only preview tool, this is complete: it covers what is returned, what is not returned, how parameters behave, and the next step in the overall workflow. The lack of an output schema is compensated by the explicit list of returned fields.

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

Parameters5/5

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

Schema coverage is 100%, yet the description still adds value by explaining the routed-session default for slug and the echo behavior for question. It reinforces the 300-character limit and optionality, so the agent can use the parameters correctly without relying on schema parsing alone.

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 exactly what the tool does: preview a paid data listing with title, price, up to 3 sample questions, and a summary excerpt. Explicitly distinguishes it from downstream paid querying by naming data_session_query as the buy path, so an agent can tell this free preview apart from sibling data tools.

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

Usage Guidelines5/5

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

The description explicitly says to call this now when a free taste is needed and no API key is available, then lays out the exact sequence for the paid path: register → data_session_fund → data_session_query (sandbox_receipt=true). It also explains the routed-session default, so the agent knows when to pass slug versus rely on the session.

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
Disambiguation2/5

Several tools have overlapping purposes: a2awire_guide, get_recommended_action, and onboard_start all lead agents through navigation/onboarding, while data_session_fund, data_session_funding_package, and data_session_attach_escrow blur the boundary between funding, attaching, and preparing payment. Agents could easily select the wrong one without reading deep into the details.

Naming Consistency3/5

Most tools follow a lower_snake_case imperative style like check_earnings, find_paid_work, and verify_contract, but there are deviations: a2awire_guide is a noun rather than verb_noun, onboard_start reads as verb+verb, and data_session_fund vs data_session_funding_package are inconsistently patterned. The naming is readable but not uniform.

Tool Count4/5

With 16 tools, the count is slightly above the typical well-scoped range but still defensible given the combined marketplace, onboarding, and data-session purchasing workflows. A few tools could be consolidated, but the overall size is not egregious.

Completeness2/5

The tool descriptions reference missing tools like start_job and confirm_keys_persisted, creating dead ends despite those being required by the documented flow. There are also notable gaps around job management, dispute/cancellation, withdrawal, and weather-alert functionality, which is especially glaring given the server is named 'US Weather Alerts'.

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