Skip to main content
Glama

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

A5/5.0
Behavior5/5

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

Annotations are uninformative (all false), so the description carries the burden. It richly discloses behavior: filing without an account returns a claim_token, passing it back later reads status, rate limits (5 per identifier per day), free, and how the team processes feedback ('reads digests daily'). 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?

The description is longer than average but every sentence serves a purpose: purpose, usage, exclusions, token flow, rate limits, and cost. It is front-loaded with the main action and well organized, making it efficient despite the detail.

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 4 parameters (one nested), no output schema, and no helpful annotations, the description is remarkably complete. It explains the return token semantics, rate limiting, scope, and how to frame feedback, covering all critical operational context an agent needs to invoke this tool correctly.

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 already describes all parameters, but the description adds significant semantic value: it explains the claim_token flow ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'), clarifies message guidance ('Be specific... 1-2 sentences typical, 2000 chars max'), and instructs not to paste end-user prompts. This goes well beyond the schema descriptions.

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 this tool from siblings by focusing on feedback submission rather than research or ticket operations, and also identifies the tool's scope (Pipeworx tools only).

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 states when to use the tool ('Use when a tool returns wrong/stale data... etc.') and when not to ('ONLY for tools served by this Pipeworx connection... file it with that server instead'). It also gives a concrete rule for disambiguation: 'Pipeworx tool names are the ones this connection lists.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the Pipeworx query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) which all provide factual answers, making it unclear which to use. The set also mixes Zendesk tools with a large number of prediction market and data tools, creating confusion.

Naming Consistency2/5

Naming conventions are inconsistent: Zendesk tools use 'zd_' prefix, Pipeworx tools use various prefixes like 'ask_', 'bet_', 'compare_', etc., and some are named with full words. There is no uniform pattern across the set.

Tool Count2/5

35 tools is high for a server named 'Zendesk', especially since only 5 are Zendesk-specific. The majority are unrelated to Zendesk, indicating the tool count is inappropriate for the implied purpose.

Completeness1/5

For a Zendesk server, the tool set is severely incomplete, offering only basic CRUD operations (get, list, search for tickets and users). Missing essential Zendesk features like ticket creation, update, delete, or macros, while containing many irrelevant tools from other domains.