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Gdc

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 annotations (all false), the description discloses key behaviors: the claim_token workflow for tracking, rate limiting ('Rate-limited to 5 per identifier per day'), no cost ('doesn't count against your tool-call quota'), and daily digest review. This is meaningful context that annotations alone don't convey.

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 every sentence carries distinct information. It opens with purpose, then quickly moves to usage rules, exclusions, and the token workflow. Slightly long, but appropriate given the tool's multi-step workflow and constraints.

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?

With no output schema, the description covers the essential return concept (claim_token), the later lookup behavior, the scope of valid feedback, and the rate limit. The input schema fully documents all 4 optional parameters. The combination gives a complete picture for an agent to invoke correctly.

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 coverage is 100%, so baseline is 3. The description adds semantics by explaining how to use claim_token ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'), instructing that messages must reference Pipeworx tools/packs, and mapping `type` values to scenarios. This adds value beyond the schema, though the schema already does a strong job.

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 clear, specific verb+resource ('Tell the Pipeworx team something is broken, missing, or needs to exist') and enumerates concrete use cases (bug, feature/data_gap, praise). It differentiates from sibling tools by establishing this as the feedback channel for Pipeworx-specific tools, not research or project 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?

It explicitly states when to use (bugs, missing features, praise) and when not to use ('ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead'). Also gives fallback guidance ('Not sure? 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.

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TDQS

A4/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx and ask_pipeworx_grounded overlap in routing (differ only in answer mode), and the multiple Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread) could cause confusion without careful reading of descriptions.

Naming Consistency3/5

Naming mix of verb-first (ask_pipeworx, compare_entities) and noun-first (entity_profile, recent_changes) patterns. Most use snake_case consistently, but the pattern is not uniform—some tools are commands, others are descriptors. Notable deviations like 'pipeworx_feedback' and 'pmc' are missing here but the sample shows inconsistency.

Tool Count3/5

30 tools is on the high side, but the server covers a broad domain (data lookup, betting, AI, genomics, memory). Some tools could be merged (e.g., ask_pipeworx and its grounded variant), and the betting subdomain feels over-instrumented. The count is borderline between appropriate and heavy.

Completeness3/5

The server provides a wide range of operations for its diverse domains, but gaps exist: the genomics tools only offer basic metadata search (no download/analysis), and the betting tools lack historical data or backtesting. It covers common patterns but with notable omissions for a cohesive experience.

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