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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

A4.8/5.0
Behavior5/5

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

All annotations are false, so description carries full burden; it delivers: mentions the claim_token flow for unauthenticated filing, how to follow up, daily digest reads, rate limit (5/identifier/day), and that it's free/quota-exempt. These behaviors are not inferable from schema or 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 yet each sentence adds unique value—purpose, use cases, exclusions, token lifecycle, and constraints. It is front-loaded with the core 'tell the team something is broken' purpose, then delivers operational details in a digestible sequence. Slightly long but 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?

No output schema exists, yet description covers what to expect (claim_token, later resolution read), and all four parameters are semantically clear from schema+description. It also handles edge cases like non-Pipeworx tools and rate limiting, making it self-sufficient for an agent to invoke correctly.

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%, but description adds crucial semantic nuance: tells users to frame issues in terms of Pipeworx tools/packs rather than pasted prompts, and shows exact claim_token usage pattern. This goes beyond the raw enum/field descriptions.

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?

Description opens with a concrete action ('Tell the Pipeworx team something is broken, missing, or needs to exist'), names the resource (Pipeworx team), and enumerates specific feedback types (bug, feature/data_gap, praise). This clearly distinguishes it from sibling research tools by specifying the feedback-only scope.

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 'Use when' list covers bug, feature/data_gap, and praise scenarios. It also gives an explicit exclusion: only Pipeworx-served tools, not other MCP servers' tools, with an alternative ('file it with that server instead'). No further guidance needed.

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
Disambiguation2/5

Multiple tools have overlapping purposes (e.g., three variants of ask_pipeworx, several polymarket tools, and multiple discovery/entity tools). Despite detailed descriptions, the similiar functionalities create confusion for an agent selecting among them.

Naming Consistency3/5

Tool names are consistently in snake_case but the verb/noun pattern is mixed: some start with verbs (ask_, list_, remember_), others with nouns (entity_profile, polymarket_edges). This inconsistency reduces predictability.

Tool Count2/5

35 tools is high for a single server, especially when the scope spans two disparate domains (HDX humanitarian data and Pipeworx data platform). Many tools could be logically split into separate, more focused servers.

Completeness3/5

The tool set covers a wide range of functionality (data retrieval, comparison, monitoring, memory) but has notable gaps: no direct data download tool for HDX resources, no account management, and no exploration of Pipeworx packs beyond discover_tools.

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