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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.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only contain false hints, so the description carries full burden. It discloses that filing without an account returns a claim_token, that passing it back later reads resolution status, that the team reads digests daily, that it is rate-limited to 5 per day, and that it is free with no quota impact—all beyond what annotations provide.

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 longer than average but every sentence carries necessary context: scope, when to use, what to include, claim_token behavior, rate limits, and cost. It is front-loaded with the primary purpose, though it is more verbose than strictly required.

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 adequately explains the return behavior (claim_token) and follow-up flow. It covers usage scenarios, scope restrictions, content guidance, rate limits, and quota—leaving little ambiguity for a feedback tool. This completeness matches the tool's complexity.

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 description coverage is 100%, so baseline is 3. The description adds value by explaining the claim_token usage pattern (e.g., call with only claim_token to read a previous report), advising not to paste end-user prompts, and clarifying how to describe issues in terms of Pipeworx tools/packs.

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 opening sentence 'Tell the Pipeworx team something is broken, missing, or needs to exist' provides a specific verb and resource, clearly defining the tool's purpose. It also distinguishes itself from siblings by explicitly scoping to 'tools served by this Pipeworx connection' and clarifying it is not for other MCP servers' 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?

The description gives explicit when-to-use scenarios: wrong/stale data (bug), missing tool (feature/data_gap), and praise. It also provides a clear when-not-to-use by directing feedback about other MCP servers to those servers instead, and explains the claim_token follow-up workflow.

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 serve overlapping research purposes (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, compare_entities), which could confuse an agent. However, descriptions help differentiate them by use case (single vs multi-part, grounded vs standard, etc.). Some overlap remains.

Naming Consistency3/5

Tool names mix patterns: some are verb_noun (ask_pipeworx, bet_research), others are noun_phrase (price_feed, recent_alerts) or adjective_noun (ticker_v2). No strong naming convention, but all use snake_case consistently, making them readable.

Tool Count3/5

40 tools is on the high side for a single server, covering both Gemini exchange data and Pipeworx's broad knowledge tools. While each tool serves a purpose, the scope feels broad, and some tools could be separated into dedicated servers.

Completeness4/5

The Gemini exchange tools cover essential read-only data (order book, candles, ticker, trades), but lack order placement, likely intentionally. The Pipeworx tools provide extensive research capabilities across many domains, leaving few gaps for the stated purposes.