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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

A4.8/5.0
Behavior5/5

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

Extends far beyond the annotations: explains the claim_token workflow for anonymous reports and later follow-up, daily rate limit of 5 per identifier, free/no quota impact, and that the team reads digests daily. These are non-obvious behaviors the agent needs to invoke and set expectations correctly.

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 long but information-dense; every sentence carries operational instructions (routing, claim_token, rate limits). It is front-loaded with purpose and use cases, though the volume of detail is higher than strictly necessary, so it doesn't earn a top conciseness score.

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 four optional params and no output schema, the description covers all key context: when to file, how to identify Pipeworx tools, the claim_token lifecycle, rate limiting, and cost. It is sufficient for an agent to select and invoke the tool correctly without further clarification.

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 schema already describes all four parameters (100% coverage), so the baseline is 3. The description adds value by explaining the claim_token round-trip ('Filing without an account returns a claim_token; pass it back later...') and by advising message specificity and 1-2 sentence typical length, which goes beyond schema constraints.

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 then enumerates concrete report types (bug, feature/data_gap, praise), making the tool's role unmistakable and clearly distinct from siblings like ask_pipeworx.

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?

Explicit when-to-use guidance is provided for each category ('Use when a tool returns wrong/stale data (bug)...'), along with a clear exclusion: reports must be for tools served by this Pipeworx connection, not other MCP servers. This tells the agent exactly when to choose this tool over alternatives.

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

Many tools have overlapping responsibilities: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all serve similar lookup purposes. entity_profile, compare_entities, and recent_changes all retrieve company data. Several Polymarket tools overlap in edge detection. The large number of tools with fuzzy boundaries makes it difficult for an agent to select the correct one.

Naming Consistency3/5

Tool names are a mix of conventions: some use verb_noun (lookup_postcode, validate_postcode, resolve_entity), others are verb_phrase (ask_pipeworx, deep_research, suggest_questions), and a few are compound (polymarket_arbitrage, scan_competitor_ai_presence). No uniform pattern, though the structure is readable.

Tool Count1/5

Despite being named 'postcodes', only 4 of 35 tools are directly about postcodes. The vast majority belong to a broad data platform (Pipeworx) with specialized tools for finance, betting, news, etc. The count is excessive for a focused service, and many tools are only useful for users of that platform, leading to clutter.

Completeness2/5

For a postcode server, the tools cover basic needs (lookup, nearest, random, validate). However, the server's actual scope is much larger; within that broader scope, there are notable gaps: no general text search, no direct access to raw SEC filings, and many tools depend on paid plans or external accounts. The coverage is uneven and incomplete for a unified data platform.