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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

A4.9/5.0
Behavior5/5

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

Annotations (readOnlyHint=false, destructiveHint=false) already signal a non-readonly, non-destructive operation. The description adds valuable context beyond annotations: the claim_token flow ('Filing without an account returns a claim_token; pass it back later...'), rate limits ('Rate-limited to 5 per identifier per day'), and impact ('signal directly affects roadmap'). This enriches the behavioral model without contradicting 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?

Despite being several sentences long, every sentence earns its place: purpose, use cases, exclusions, tips, token flow, rate limits, and cost. It is front-loaded with the core purpose and structured logically, making it dense but not verbose.

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?

The tool has no output schema, but the description explains return behavior (claim_token) and the follow-up workflow. It covers edge cases (different MCP servers), rate limiting, and free usage, making it complete for a feedback tool of this 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?

Schema description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining the claim_token usage ('pass it back later... to read whether it was fixed and what changed') and instructing how to populate message/context ('Describe the issue in terms of Pipeworx tools/packs'). Though it doesn't enumerate each parameter, it provides useful guidance, elevating it to a 4.

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's purpose: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It uses a specific verb and identifies the resource (Pipeworx team feedback), and it distinguishes itself from sibling research tools by being the only feedback submission tool.

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 provided: '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 when-not-to-use and alternatives: 'if the tool came from a different MCP server... file it with that server instead.' This clearly differentiates from siblings.

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

A3.6/5.0
Disambiguation2/5

Several tools have overlapping jobs: ask_pipeworx_beta is currently identical to ask_pipeworx, ask_pipeworx_grounded is the same router with stricter extraction, and discover_tools/suggest_questions both serve discovery. Company-facing tools also overlap (entity_profile vs recent_changes vs compare_entities), so an agent could easily route a query to the wrong tool despite detailed descriptions.

Naming Consistency3/5

Names are mostly snake_case and grouped prefixes like get_*, ask_pipeworx*, and polymarket_* are readable. However, conventions are mixed across the set: some are verb_noun (search_companies), some are noun phrases (entity_profile, deep_research, recent_changes), and the Companies House family sits awkwardly beside unrelated Pipeworx and prediction-market families.

Tool Count1/5

With 36 tools, the server is already heavy, but only five tools actually serve the named Companies House domain. The other 31 belong to Pipeworx querying, memory, subscriptions, and Polymarket trading, which is a severe mismatch between the server's stated purpose and its actual surface.

Completeness3/5

For UK company data, the core surface is mostly covered: search, company profile, filings, officers, and PSCs. However, charges and official document retrieval are missing even though get_company links to them, and the unrelated tools do nothing to complete the Companies House domain.