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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

A4.7/5.0
Behavior5/5

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

The description discloses the claim_token flow (filing without an account returns a token for later status checks), rate limits (5 per identifier per day), and that it is free and doesn't count against quota. It also notes the team reads digests daily and signal affects roadmap. This adds rich context beyond the minimal 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 a single dense paragraph but every sentence earns its place—it covers use cases, exclusions, token flow, rate limits, and quota impact. Slightly long but not bloated; it's front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a feedback tool with no output schema, it explains the claim_token response and how to retrieve status later. It also covers rate limiting, scope (only Pipeworx tools), and content guidelines. The main gap is not describing the exact response object beyond claim_token, but the tool's complexity is modest.

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 the baseline is 3. The description adds extra value by advising what to put in the message ('don't paste the end-user's prompt', 'describe in terms of Pipeworx tools/packs') and explaining how to use claim_token for later replies. This goes beyond the schema.

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 clearly states the tool lets the user tell the Pipeworx team something is broken, missing, or needs to exist—a specific verb and resource. It distinguishes itself from siblings by focusing exclusively on feedback about Pipeworx tools, not data queries or other operations.

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?

Explicitly names use cases (bug, feature/data_gap, praise) and when NOT to use it (if the tool came from a different MCP server, file with that server instead). Even provides a diagnostic: 'Not sure? Pipeworx tool names are the ones this connection lists.'

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap among closely related ones (e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research; multiple Polymarket tools). Descriptions are detailed enough to differentiate, but an agent might still misselect on subtle differences.

Naming Consistency4/5

Names consistently use lowercase with underscores, but no strong verb_noun pattern. Some are noun-based (airquality, nowcast), others verb-based (ask_pipeworx, compare_entities). This is readable but not perfectly predictable.

Tool Count4/5

35 tools is high but justified by the server's broad scope (data queries, betting analysis, weather, memory, subscriptions). The number feels appropriate given the comprehensive functionality described.

Completeness5/5

The tool set covers an impressively wide range of capabilities: data querying with multiple modes, entity profiling, comparisons, search, betting analysis, weather, memory, subscriptions, and feedback. Missing features (e.g., updating memories) are minor; the surface is remarkably complete.

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