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Scream Void

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. Added

TDQS

A4.8/5.0
Behavior5/5

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

The description goes far beyond the annotations (which only indicate non-read-only, non-idempotent, non-destructive). It discloses the claim_token mechanism ('Filing without an account returns a claim_token; pass it back later... to read whether it was fixed'), the rate limit ('Rate-limited to 5 per identifier per day'), and that it's free and doesn't count against tool-call quota. These are critical behavioral traits not captured in structured 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 long but each sentence serves a purpose: clear purpose, usage criteria, exclusions, token flow, rate limits, and daily digest. It is front-loaded with the core action. A slightly more concise version might be possible, but the length is justified given the tool's behavior and the need to prevent misuse (e.g., reporting external tools).

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 explains the primary return (claim_token) and the later status/read flow. It also covers rate limits, free usage, and the daily digest process. The tool has nested objects (context) and an enum (type), but the description complements these by explaining the overall purpose and edge cases. The completeness is high for this 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?

While the schema already provides 100% coverage for parameter descriptions, the tool description adds meaningful workflow context for the claim_token parameter: 'pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed.' This clarifies how parameters interrelate (e.g., claim_token used alone without other arguments), which is not evident from the schema alone.

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 explicitly states the tool's function: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly identifies the resource (Pipeworx team) and the action (sending feedback). It also distinguishes the tool from sibling tools by specifying it is only for this Pipeworx connection's tools, not other MCP servers.

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 provides explicit when-to-use guidance: '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 gives a clear exclusion: 'ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead.' This covers both positive and negative usage scenarios.

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

Many tools overlap significantly in purpose, especially the ask_pipeworx variants (standard, beta, grounded) and deep_research, as well as the polymarket arbitrage/edges/fill_risk/kalshi_spread suite. It would be hard for an agent to reliably choose the correct tool without deep understanding of subtle distinctions.

Naming Consistency3/5

Tool names mostly use snake_case, but there is no consistent prefix or verb pattern. Some names are descriptive phrases (e.g., scream_void_scream, compare_entities) while others are vague (e.g., forget, recall). The mix of 'pipeworx_' prefix on some tools and lack of it on others adds inconsistency.

Tool Count3/5

32 tools is on the high side for a data research server, given the overlapping functionality. Some tools could be merged (e.g., the ask_pipeworx variants, polymarket tools). However, the count is not excessive enough to be unmanageable, and each tool serves a specific niche.

Completeness4/5

The server covers a broad range of data sources and prediction market analysis, with tools for research, comparison, monitoring, and memory. Minor gaps exist (e.g., no tool to update stored memories or manage subscriptions beyond CRUD), but core workflows are well-supported.

Resources