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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

A4.7/5.0
Behavior5/5

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

The description adds rich behavioral context beyond the annotations, including rate limiting ('Rate-limited to 5 per identifier per day'), the claim_token workflow, the fact that it is free and does not count against quota, and that the team reads digests daily. Annotations only say readOnlyHint=false, so this is substantial added value.

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?

Though the paragraph is dense, every sentence earns its place: purpose, use cases, boundary conditions, workflow, expectations, and rate limits. It is front-loaded with the purpose and structured logically.

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?

The description is complete for a feedback tool with four parameters, nested context objects, and no output schema. It explains the claim_token return value and how to read it later, covers edge cases like missing accounts, and sets rate-limit expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage of all four parameters, including detailed descriptions for type, context, message, and claim_token. The description adds no parameter-specific semantics beyond what the schema already covers, though it reinforces the claim_token workflow.

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 feedback tool from sibling tools like ask_pipeworx or research tools by framing it as reporting issues to the Pipeworx team.

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 the tool: for bugs, feature/data gaps, and praise. It also gives an explicit exclusion: 'if the tool came from a different MCP server... file it with that server instead.' This is exceptional guidance.

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

A3.6/5.0
Disambiguation2/5

Several tools occupy nearly identical roles: ask_pipeworx and ask_pipeworx_beta are described as currently identical, ask_pipeworx_grounded and deep_research overlap with the router, and eia_series overlaps with the specialized eia_electricity/eia_ethanol/eia_natural_gas/eia_petroleum tools. The Polymarket opportunity scanners and the two AI-visibility checkers also blur together, making confident tool selection difficult despite detailed descriptions.

Naming Consistency3/5

Most tools follow a snake_case verb-first pattern (remember, recall, forget, resolve_entity, validate_claim), but there are notable deviations: eia_electricity and eia_ethanol are noun-first category names, recent_alerts and recent_changes are adjective-noun, and pipeworx_trending and polymarket_edges are not verb-driven. The eia_ and polymarket_ prefixes add some predictability, so the naming is readable but inconsistent.

Tool Count2/5

At 36 tools, this is well past the heavy threshold and feels like a kitchen-sink aggregation of several separate products rather than one focused server. Many tools could be consolidated: the five eia_* lookups, the multiple ask_pipeworx variants, and the several Polymarket scanners all serve close purposes. A 36-tool surface is too much for an agent to navigate efficiently.

Completeness4/5

Within the major subdomains the set is quite complete: entity research has profile/compare/changes/resolve, memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and Polymarket analysis has edge discovery, fill-risk, venue-spread, and persistence tracking. Minor gaps exist—no subscription update flow, no dedicated EIA coal/nuclear/renewables series beyond the generic eia_series fallback—but agents can work around them.