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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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations, the description discloses meaningful behavioral traits: rate-limited to 5 per identifier per day, returns a claim_token for anonymous reports, and explains the follow-up mechanism to read resolution status. It also notes that feedback is free and doesn't count against quota, and that the team reads digests daily. No annotation contradiction exists.

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?

The description is rightly dense but every sentence earns its place: purpose, usage triggers, scope exclusions, content guidance, claim-token flow, rate limit, and cost. It is front-loaded with the verb and resource, then flows logically through when, what, and how. No redundant or filler content.

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 having no output schema, the description fully equips the agent: return behavior (claim_token), how to retrieve status later, rate limits, scope boundaries, and content expectations. It handles the nested context object implicitly by referring to 'which tool, pack, or vertical' via schema descriptions. For a complex, multi-purpose feedback tool, this is exceptionally complete.

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 extra semantics for claim_token by showing exact usage (pipeworx_feedback({claim_token:'pwfb_…'})) and for message content by instructing to describe issues in terms of Pipeworx tools/packs and avoid pasting end-user prompts. This goes beyond the schema's field-level descriptions, though not every parameter receives extra treatment.

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 itself from all sibling tools (none of which are feedback-related) and adds scope boundaries explicitly. This is a model of purpose clarity.

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 provides explicit when-to-use guidance with concrete trigger categories: bug, feature/data_gap, praise. It also gives a clear alternative action for non-Pipeworx tools ('file it with that server instead') and tells users how to verify tool ownership. This fully addresses when and when-not to use.

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

A3.7/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions, while the polymarket_edges, polymarket_arbitrage, and related tools blur edge-detection boundaries. The server's Bitstamp identity also clashes with the bulk of tools being unrelated data-research, making selection harder.

Naming Consistency3/5

Tool names are all lowercase snake_case, which is consistent formatting, but no coherent verb_noun pattern emerges. Some are verb-first (ask_pipeworx, compare_entities, discover_tools) while others are noun-first or resource-based (ticker_hour, order_book, polymarket_edges), and the naming style differs across the two major domains.

Tool Count2/5

At 38 tools, the set is well over the 15-tool threshold for a focused server, and the majority of tools are unrelated to the server's Bitstamp name. The count feels bloated and scattershot—it would be better split into separate data-research and exchange servers.

Completeness3/5

The data-research and question-answering surface is broadly covered, with meta-tools and validation. However, the Bitstamp exchange half is incomplete: it only provides public market data (ticker, order book, trades, OHLC) with no trading, account, or private-data operations, an obvious gap given the server's name.