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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 are all false and provide no safety hints, so the description carries the full burden. It discloses the claim_token flow, rate limiting (5 per identifier per day), free status with no tool-call quota impact, and that the team reviews daily. These are meaningful behavioral traits beyond the schema and 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?

The description is dense but every sentence earns its place. It is front-loaded with purpose, then usage boundaries, then mechanics (claim_token), then operational details (rate limit, quota). No redundancy or filler.

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 complexity (4 params, nested objects, no output schema, annotations with no helpful hints) the description is exceptionally complete. It explains what to use it for, what not to use it for, how the claim_token works, rate limits, billing impact, and how feedback affects roadmap. Nothing ambiguous remains.

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 covers 100% of parameters with detailed descriptions, so the baseline is 3. The description adds value by instructing users to 'describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt,' which is not in the schema. It also clarifies the claim_token usage pattern in context. Minor additional semantic guidance beyond the schema.

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 a specific verb and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes the tool from research-oriented siblings by scoping it to feedback (bug, feature, data_gap, praise) and explicitly stating it is only for tools served by this Pipeworx connection.

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?

Provides explicit when-to-use guidance with examples: bug, feature/data_gap, praise. Also gives a clear exclusion boundary ('if the tool came from a different MCP server... file it with that server instead') and a disambiguation rule ('Pipeworx tool names are the ones this connection lists'). This is textbook usage guidance.

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

A4.1/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, from Wikipedia page views to AI visibility checks, entity resolution, and Polymarket betting. No two tools appear overlapping in functionality; descriptions further clarify each tool's unique role.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with clear verb_noun structure (e.g., get_article_views, subscribe, resolve_entity). No mixing of conventions, and names are descriptive enough to infer purpose.

Tool Count2/5

With 33 tools, the server is overloaded for its name 'wikiviews', which suggests a focused Wikipedia views tool. The set includes unrelated functionality like Polymarket arbitrage, memory storage, and Pipeworx data queries, making the scope feel excessive.

Completeness2/5

For the core domain of Wikipedia views, only 3 tools exist (get_article_views, get_project_views, get_top_articles), missing basic operations like list_articles_per_day. The unrelated tools are extensive, but the server's stated purpose is poorly served.