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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?

The description enriches the neutral annotations (all false) with important behavioral details: the claim_token flow for follow-up, daily digest review, rate limit of 5 per day, and that feedback is free and doesn't count against quota. It also implies a persistent write operation (submission) without contradicting 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 detailed and front-loaded with the core purpose, but it is quite lengthy. Still, every sentence contributes (token flow, rate limits, exclusions, roadmap signal), so it remains efficient for the amount of behavioral context needed.

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?

Despite lacking an output schema, the description fully covers the tool's role, usage scenarios, non-goals, authentication (claim_token), rate limiting, and impact. It is complete for a feedback submission tool with nested context and multiple feedback types.

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 the baseline is 3. The description adds meaningful parameter guidance beyond the schema, notably 'Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt,' which is critical for correct message content. It also clarifies the claim_token usage pattern in the main text.

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 verb+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It explicitly lists the feedback types (bug, feature/data_gap, praise) and distinguishes the tool from siblings by stating it is ONLY for tools served by this Pipeworx connection, 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?

Provides explicit conditions for use: when a tool returns wrong/stale data, when a desired tool is missing, or for praise. It also gives a clear exclusion ('if the tool came from a different MCP server... file it with that server instead') and actionable guidance for identifying Pipeworx tools by name.

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
Disambiguation3/5

Many tools are crisply separated (memory CRUD, subscription lifecycle, single-entity vs compare vs profile), but several broad entry points overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very close variants, and discover_tools/suggest_questions/ask_pipeworx all serve discovery/routing. Descriptions help, but an agent can still easily select one of the duplicate or adjacent tools instead of the intended one.

Naming Consistency3/5

All names are readable snake_case and there are coherent families (polymarket_*, ask_pipeworx_*, search_*, get_*), but there is no consistent verb_noun convention: noun-phrase names like recent_alerts and pipeworx_trending coexist with single verbs like remember and forget and domain-prefixed nouns like polymarket_edges. Mixed, but still reasonably navigable.

Tool Count2/5

At 35 tools, the surface is well past the comfortable 3-15 tool scope and even beyond the 16-25 heavy range unless the server has one explicit mega-purpose. The set also sprawls across music lookup, Pipeworx research, prediction markets, npm checks, LLM visibility, memory, and subscriptions, so no single coherent job emerges.

Completeness4/5

For the dominant read-only research workflow, the set is remarkably complete: discover tools, grounded and ungrounded asking, deep research, entity resolution, profiles, recent changes, comparisons, claim verification, search_within, plus full memory and subscription lifecycles. Minor gaps include the shallow music side relative to the rest of the server and the absence of an explicit source catalog.