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diceuear

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?

Beyond the annotations (which indicate non-read-only, non-idempotent, non-destructive), the description adds important behavioral context: the claim_token follow-up mechanism, rate limiting to 5 per identifier per day, and that feedback is read daily and affects roadmap. This fully discloses side effects and operational nuances without contradicting the 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 somewhat lengthy but every sentence adds value—covering when to use, exclusions, follow-up, rate limits, and impact. It is well-structured and front-loaded with the purpose, though it could be tightened slightly without losing information.

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 lacking an output schema, the description explains the response behavior (claim_token when not logged in, ability to check resolution later), rate limits, and that feedback is read daily. It also addresses the lack of required parameters. This makes the tool fully self-explanatory and complete for an agent to decide to use it.

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?

The schema already provides 100% coverage with good parameter descriptions. The description adds extra semantics by explaining how to use claim_token for follow-up and advising users not to paste end-user prompts. This going beyond the schema justifies a 4 rather than a baseline 3.

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 and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' This clearly states the tool's function and differentiates it from sibling research/query tools like ask_pipeworx or deep_research. It is unambiguous about the feedback submission purpose.

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 explicitly lists when to use the tool: for bugs, feature/data_gap requests, or praise. It also provides a clear exclusion: 'ONLY for tools served by this Pipeworx connection' and directs users to file with other MCP servers for unrelated tools. This is a strong, unambiguous usage guideline.

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

A4.1/5.0
Disambiguation4/5

Tools have mostly clear distinctions: ask_pipeworx variants differ by grounding/evidence guarantees, and meta-tools (discover_tools, suggest_questions) serve onboarding. However, ask_pipeworx_beta currently matches ask_pipeworx exactly, creating transient ambiguity, and deep_research vs ask_pipeworx overlap in routing capability though with different scopes.

Naming Consistency4/5

All tools use snake_case and most follow verb-first naming (ask_pipeworx, compare_entities, generate_avatar, subscribe). A few are descriptive nouns (recent_alerts, recent_changes, pipeworx_trending) but still readable and predictable. No mixed conventions; overall consistent style.

Tool Count2/5

33 tools is excessive for a single server, and many are auxiliary (avatar generation, memory, feedback) that do not serve the core data-access purpose. The primary question-answering capability is centralized in a few routers, making many separate tools feel redundant or unrelated, which dilutes navigability.

Completeness4/5

The core domain of structured data access is well covered with routing, grounded answering, deep research, entity profiles, comparisons, and claim validation. Subscription lifecycle (subscribe/unsubscribe/alerts) and memory (remember/recall/forget) round out the surface. Minor gaps like lack of direct tool invocation outside the router are covered by discover_tools, and no critical dead ends exist for typical queries.

Resources