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Cnb Cz

by io.github.pipeworx-io

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

A4.9/5.0
Behavior5/5

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

The description discloses several behavioral traits beyond the sparse annotations: the claim_token workflow for following up on reports, the 5-per-day rate limit, free-of-quota status, and the fact that feedback signals the roadmap. These are exactly the kind of contextual behaviors an agent needs to know.

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 dense, every sentence adds essential information: purpose, use cases, exclusions, token semantics, rate limits, and roadmap impact. There is no redundancy or filler; the long paragraph is justified by the tool's complexity.

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?

For a tool with no output schema and four parameters (one nested object), the description fully covers invocation workflow, return behavior (claim_token), constraints, and follow-up usage. It leaves no critical gaps for an agent to misuse the tool.

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% and each parameter has a rich description, so the baseline is 3. The tool description adds further value by instructing what to include in the message ('in terms of Pipeworx tools/packs') and explicitly saying not to paste the end-user's prompt, which complements the schema's message field.

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+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes from sibling tools by focusing on feedback about Pipeworx tools themselves, not on using tools to answer questions or research.

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 with concrete examples: bug, feature/data_gap, praise. It also gives an exclusion rule for tools from other MCP servers and suggests how to resolve ambiguity ('Not sure? Pipeworx tool names are the ones this connection lists'). This fully addresses usage relative to 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

A4.2/5.0
Disambiguation4/5

Tools have distinct purposes overall, but some pairs (e.g., ask_pipeworx vs ask_pipeworx_grounded, entity_profile vs recent_changes) could cause agent confusion without careful reading. Descriptions mitigate overlap, so only minor ambiguity.

Naming Consistency4/5

Most tools use snake_case with verb_noun or noun_verb patterns, but several single-word verbs (forget, recall, remember, subscribe) and a few inconsistent forms (czeonia, pribor) break uniformity. Still, the pattern is largely predictable.

Tool Count4/5

31 tools is high but justified for a multi-domain data gateway covering finance, economics, FDA, betting, and subscriptions. Each tool has a clear role, though the count pushes the upper bound for easy scanning.

Completeness5/5

The tool set comprehensively covers its stated domains: entity resolution, financial data, exchange rates, interest rates, SEC filings, FDA, Polymarket analysis, subscriptions, and utility memory. No obvious gaps given its purpose as a data retrieval and analysis server.

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