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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

A4.8/5.0
Behavior5/5

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

Annotations are all false, providing no safety or idempotency info. The description compensates by disclosing rate limits ('5 per identifier per day'), the claim_token workflow, that reports are read daily, and that the tool is free and quota-free. This is rich behavioral context beyond structured fields.

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?

Compact but dense; every sentence conveys a distinct point (purpose, when-to-use, exclusions, token flow, limitations). It is longer than a one-liner but well-structured with the opening sentence carrying the core purpose.

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?

No output schema exists, so the description is the only source for understanding the response/claim_token flow. It covers scope boundaries, error categories, submission format, rate limits, and follow-up usage. This is complete for a feedback tool with nested optional context.

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 constraints not in the schema: claim_token must be passed alone ('with no other arguments') and message should be specific, 1-2 sentences. It also advises describing issues in terms of Pipeworx tools/packs, which clarifies the `context` object's intent.

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 action ('Tell the Pipeworx team something is broken, missing, or needs to exist') and explicitly enumerates feedback types (bug, feature/data_gap, praise). It distinguishes from sibling tools like ask_pipeworx by framing this as feedback about Pipeworx's own tools, not a question.

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 states when to use: 'Use when a tool returns wrong/stale data...', when a tool is missing, or praise. Includes clear exclusions: 'ONLY for tools served by this Pipeworx connection' and instructs to file external-tool issues elsewhere. Also warns against pasting end-user prompts.

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

B3.3/5.0
Disambiguation2/5

The major clusters are distinct (blockchain explorer, memory, subscriptions), but several tools have unclear boundaries: ask_pipeworx_beta is currently identical to ask_pipeworx, the three ask_pipeworx variants and deep_research all route questions, and the five Polymarket tools overlap heavily on edge detection. An agent would struggle to pick the right query tool or prediction-market tool without reading very long descriptions.

Naming Consistency2/5

Naming is a mix of single-word nouns (address, block, node, transaction, stats), verb-noun snake_case (validate_claim, generate_llms_txt), and noun-phrase snake_case (entity_profile, bet_research), with no consistent style or verb convention. There is no predictable pattern an agent can generalize from.

Tool Count2/5

36 tools is well above the comfortable range, and most are meta-tools for Pipeworx, Polymarket, memory, and subscriptions rather than Blockchair blockchain functionality. A large share of the count is redundant query and edge-analysis variants, so the size adds confusion rather than capability.

Completeness4/5

As a read-only research and monitoring gateway, the surface is fairly complete: universal routing, grounded answers, entity resolution, profiles, comparisons, claim validation, memory, and subscriptions all have lifecycle coverage. Relative to the Blockchair name, the blockchain side is thin but covers address, block, transaction, node, and stats, with only minor gaps like mempool or raw script details that agents can work around.