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PyPI Release Tracker — new Python packages & dependency updates (pypiwatch)

data_preview

Read-onlyIdempotent

✅ No API key needed — call this now. Listing: pypiwatch: New PyPI package releases & Python dependency updates. Price 0.01 USDC/query (max 20 queries/session). Sample questions: What are the newest package releases on PyPI?; Which new Python packages were just registered on PyPI?. FREE preview — no key, no payment. Try one of the sample questions now.

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).

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?

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful context that no API key or payment is required and mentions a 20-query/session limit, although it is ambiguous whether that limit applies to the preview or the paid listing. It does not clarify output format or the fact that 'question' is echoed back, and the mixed price/free messaging could confuse an agent.

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 repetitive ('No API key needed' and 'FREE preview — no key, no payment' say the same thing) and padded with promotional language, emojis, and repeated calls to action. The essential information could be delivered in two concise sentences.

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?

For a simple two-optional-parameter tool, the description plus schema cover invocation basics. However, with no output schema, the description should at least state that the result is a preview of public metadata; instead it focuses on promotion and leaves return behavior implicit. The ambiguous pricing/quota reference also weakens completeness.

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?

Both parameters are already fully documented in the schema (100% coverage), so the baseline is 3. The description adds value by providing a concrete slug example ('pypiwatch') and two sample questions that map naturally to the question parameter, which helps an agent construct valid inputs.

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 the action as a 'FREE preview' of the pypiwatch listing, with sample questions that clarify the domain. It distinguishes the tool from paid/session-based siblings by stressing 'no API key' and 'no payment.' However, it never states what the preview returns (e.g., public metadata), leaving some clarity to the schema.

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

Usage Guidelines3/5

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

Implied usage is to try the listing for free before paying, with sample questions provided as starting points. There is no explicit comparison to alternatives such as data_session_query or data_session_open, nor any statement of when not to use this tool. 'Call this now' is an instruction, not a usage policy.

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

B3/5.0
Disambiguation1/5

Multiple tools are near-duplicates in the data-session funding flow (data_session_fund, data_session_funding_package, data_session_attach_escrow) and guidance tools overlap (a2awire_guide vs get_recommended_action). A caller looking for PyPI release information cannot easily distinguish the relevant query tools from the marketplace and onboarding tools.

Naming Consistency2/5

There is a data_session_* cluster and some get_* names, but the set mixes bare verbs (register), gerund-style names (check_earnings, find_paid_work), compound verbs (hire_and_execute), and prefixed nouns (a2awire_guide, onboard_start). The naming is not chaotic enough for 1, but it lacks a consistent convention.

Tool Count2/5

16 tools is already on the heavy side, and the majority concern agent-marketplace onboarding, escrow, hiring, and earnings rather than PyPI package tracking. The count would be plausible for an A2AWire platform server, but it is far too large and unfocused for the advertised PyPI Release Tracker.

Completeness1/5

The stated purpose is tracking new PyPI releases and dependency updates, yet there are no dedicated tools for listing packages, fetching release details, or monitoring dependencies. The only data-related surface is a generic data_preview/data_session_query pair, leaving the actual domain essentially uncovered.

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