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Google_docs

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?

The annotations only provide false hints, so the description carries the burden and does so excellently. It discloses rate limits ('Rate-limited to 5 per identifier per day'), no cost ('Free; doesn't count against your tool-call quota'), triage flow ('The team reads digests daily'), and the claim_token round-trip behavior. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but front-loaded with its purpose and contains no filler. However, it is a single long paragraph; while every sentence earns its place, it could be slightly more scannable with visual structure. Still, it remains appropriately sized for the amount of critical guidance it conveys.

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 moderate complexity (4 optional params, nested context object, claim-token flow) and no output schema, the description is complete. It covers expected use cases, exclusions, account-optional behavior, rate limits, cost, and the post-filing follow-up flow. The agent has enough information to decide when and how to invoke 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?

Even though schema coverage is 100%, the description adds meaningful parameter-level context beyond the schema. It gives an explicit invocation example for claim_token (`pipeworx_feedback({claim_token:"pwfb_…"})`), explains when to use each argument, and instructs users to describe issues in terms of Pipeworx tools/packs rather than pasting the end-user's prompt.

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 uses a specific verb ('Tell the Pipeworx team something is broken, missing, or needs to exist') and clearly identifies the resource (Pipeworx team/tools). It also distinguishes itself from siblings by explicitly limiting use to tools served by this Pipeworx connection and contrasting with other MCP servers.

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 provides explicit when-to-use guidance for each feedback type ('Use when a tool returns wrong/stale data (bug)...') and equally explicit when-not-to-use guidance ('ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead'). It also gives an alternative path for uncertain cases, making the decision boundary very clear.

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

B3.4/5.0
Disambiguation2/5

Several tools are nearly indistinguishable: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, while ask_pipeworx_grounded and deep_research heavily overlap with the same router. The dense Polymarket tool cluster and discovery tools (discover_tools vs suggest_questions) further blur boundaries, though many individual tools do have distinct niches.

Naming Consistency3/5

Names are consistently lowercase snake_case, which helps, but the convention is mixed: some are verb_noun (docs_create, list_subscriptions), some are noun phrases (entity_profile, deep_research, bet_research), and one uses a suffix (ask_pipeworx_beta). It is readable but not a predictable pattern across the set.

Tool Count2/5

37 tools is already above the 25+ threshold, but the bigger problem is that the server is named Google_docs and only 6 of the 37 tools relate to Google Docs. The remaining 31 tools form a broad data-research and prediction-market platform, making the set feel bloated and mislabeled for its apparent purpose.

Completeness2/5

For a Google Docs server, the surface is incomplete: you can create, read, insert, replace, and append text, but there is no delete, no list/search, no formatting control, and no permission handling. The extensive Pipeworx and Polymarket tools cover a different domain entirely, so they do not fill the gaps in the docs workflow.

Resources