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Glama

airquality

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only say the operation is not read-only/idempotent/etc., but the description adds rich behavioral detail: filing without an account returns a claim_token that can be reused to poll status, daily rate limits of 5 per identifier, free usage, and the note that the team reads digests daily. It also warns users not to paste end-user prompts, which is valuable operational guidance. No contradiction with 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?

Although longer than average, the description is front-loaded with the core purpose, then branches into use cases, exclusions, claim-token behavior, and constraints. Every sentence carries actionable information; nothing is filler or repetitive.

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?

There is no output schema, so the description itself must cover return behavior and outcome expectations. It explains the claim_token response, how to check resolution status, rate limiting, and the fact that feedback directly affects roadmap. Combined with the fully self-describing input schema, this is complete for the tool's complexity.

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 documents all four parameters (type, context, message, claim_token) with descriptions, so the baseline is 3. The description adds extra value by explaining the claim_token round-trip workflow ('Filing without an account returns a claim_token; pass it back later...') and by advising users to frame feedback in terms of Pipeworx tools/packs, which clarifies how to fill `context` and `message`.

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 opens with 'Tell the Pipeworx team something is broken, missing, or needs to exist,' giving a clear verb–resource pairing and distinguishing this from all sibling tools. It unambiguously identifies the tool as a feedback-reporting channel for Pipeworx 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?

Explicitly specifies when to use the tool (bug, feature, data_gap, praise) and, crucially, when not to use it: 'if the tool came from a different MCP server... file it with that server instead.' It also clarifies how to describe issues and how to use the claim_token later, leaving no ambiguity about invocation context.

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
Disambiguation3/5

Many tools have overlapping purposes, especially multiple ask_pipeworx variants and numerous Polymarket tools. Detailed descriptions help, but an agent could still confuse similar tools like ask_pipeworx and ask_pipeworx_beta.

Naming Consistency2/5

Tool names use a mix of styles: some are descriptive (get_air_quality), some use proprietary prefixes (pipeworx_feedback), and others are arbitrary (bet_research). No consistent verb_noun pattern.

Tool Count1/5

33 tools is excessive for a server named 'airquality', which only has 2 air-quality-specific tools. The count is appropriate for a general data platform, but mismatched with the server name.

Completeness1/5

For the air quality domain, the tool set is severely incomplete, missing historical data, pollution sources, and health recommendations. The overall set covers many other domains, but fails to address the server's apparent focus.

Resources