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Glama

Xero

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. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the all-false annotations, the description discloses rate limiting (5 per identifier per day), that it is free and doesn't count against tool-call quota, that the team reads digests daily, and how claim_token works for follow-up. 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 long but every sentence earns its place, covering purpose, usage, exclusions, token mechanics, and limits. It is well-structured and front-loaded with the core action first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description explains the claim_token return and the overall workflow well. It covers types, context, rate limits, and account behavior. A minor gap is not describing the immediate success response beyond the token, but this is a minor omission.

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?

Schema covers 100% of parameters, but the description adds practical detail: claim_token usage with a concrete example, message content guidelines, and clarification of the enum types. This goes beyond the schema's field 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 clearly states the tool's purpose: sending feedback to the Pipeworx team about bugs, missing features, data gaps, or praise. It distinguishes itself from siblings like ask_pipeworx by focusing on reporting issues rather than querying or research.

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?

It explicitly lists when to use (bug, feature/data_gap, praise) and when not to use (for tools from other MCP servers), with clear guidance to file elsewhere otherwise. It also advises how to formulate feedback (in terms of Pipeworx tools/packs, not user prompts).

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap (e.g., ai_visibility_check and scan_competitor_ai_presence are related; memory tools remember/recall/forget form a clear subgroup). Descriptions are detailed enough to differentiate, but the broad scope may cause occasional mis-selection.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (list_accounts, get_profit_and_loss), others are single words (forget, recall), and some use snake_case with mixed verbs (ai_visibility_check, ask_pipeworx, bet_research). No uniform pattern makes the set harder to navigate.

Tool Count3/5

25 tools is high but not extreme given the broad scope (accounting, betting, data queries, npm, memory, etc.). However, the server tries to cover too many domains, making it feel bloated. Each tool is individually useful, but the count is borderline excessive for coherence.

Completeness2/5

The Xero accounting subset is incomplete: only list and get operations, no create/update/delete for invoices, contacts, or accounts. Other domains (betting, npm) are covered well, but the core accounting purpose has significant gaps that will hinder agents.

Resources