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Webflow

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.

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?

The description discloses far more than the annotations do: it mentions rate limiting ('Rate-limited to 5 per identifier per day'), the claim_token mechanism for anonymous users, the fact that it's free and doesn't count against tool-call quota, and that the team reads digests daily. These are meaningful behavioral insights that go beyond the minimal annotation flags, and there is no contradiction with annotations.

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 dense but every sentence earns its place. It front-loads the purpose, then systematically covers use cases, exclusions, token flow, rate limits, and cost. No filler or repetition; it is appropriately sized for a tool with nuanced behavior.

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 feedback tool with no output schema, the description fully covers the key contextual aspects: how to frame feedback, who it applies to, what anonymous users can expect (claim_token), how to follow up, rate limits, and quota impact. The schema provides the parameter details, and the description fills in the behavioral and workflow gaps completely.

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 baseline is 3. The description adds value by clarifying the message parameter ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt') and explaining the claim_token round-trip usage. While it doesn't cover all parameters in prose, the schema already documents type and context well, so this extra guidance elevates it.

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 clear, specific statement: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It immediately conveys the verb (tell/feedback) and resource (Pipeworx team) and distinguishes itself from sibling tools like ask_pipeworx by emphasizing it is exclusively for feedback about Pipeworx tools served by this connection.

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 is given with concrete examples: '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).' It also provides a clear when-not-to-use by stating it only applies to tools on this Pipeworx connection and not other vendors' MCP servers, directing users to file elsewhere.

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

A3.5/5.0
Disambiguation2/5

Several tools have blurry boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges/polymarket_arbitrage/polymarket_edge_tracker/polymarket_fill_risk all target overlapping prediction-market signals, and ai_visibility_check vs scan_competitor_ai_presence plus entity_profile vs recent_changes vs compare_entities partially duplicate each other. The Webflow tools are distinct, but the dominant Pipeworx cluster is hard to navigate.

Naming Consistency2/5

Naming mixes multiple conventions: clean verb_noun for Webflow tools (list_sites, get_collection_item), an ask_pipeworx family, plain single verbs (remember, recall, forget), and long noun-cluster names for prediction markets (polymarket_arbitrage, polymarket_edge_tracker). There is no single predictable pattern across the set.

Tool Count1/5

36 tools is excessive for a server named 'Webflow' — only about six tools actually concern the Webflow CMS (list_sites, get_site, list_collections, list_collection_items, get_collection_item, generate_llms_txt). The remaining ~30 tools form a completely different data-research/prediction-market/memory suite, making the server wildly over-scoped and mislabeled.

Completeness2/5

For the Webflow domain, the surface is read-only: sites and collections can be listed and items fetched, but there are no create, update, delete, or publish operations, leaving obvious lifecycle gaps. The extensive non-Webflow tools do not address the stated server purpose, so the mismatch hurts completeness rather than fixing it.

Resources