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Censtatd Hk

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.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only set all hints to false, so the description carries the burden. It discloses rate limiting (5 per identifier per day), that it's free and doesn't count against quota, the daily digest review, and the claim_token mechanism. This goes well beyond the structured data.

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 detailed but every sentence serves a purpose. It is front-loaded with the core purpose, then systematically covers scope, usage, token mechanics, and rate limits. No filler or redundancy.

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 tool with 4 parameters, no output schema, and nested objects, the description explains the full workflow: filing, receiving a token, checking resolution later, and the policy constraints. It adequately covers all necessary operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents parameters thoroughly. The description adds general guidance (e.g., describe issues in Pipeworx terms, don't paste user prompts) but doesn't significantly expand on individual parameter meanings beyond what the schema provides.

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 'Tell the Pipeworx team something is broken, missing, or needs to exist,' which clearly identifies the tool as a feedback channel. It enumerates the specific feedback types (bug, feature, data_gap, praise) and differentiates from sibling research/query tools.

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?

Provides explicit when-to-use triggers ('Use when a tool returns wrong/stale data...') and a clear exclusion ('if the tool came from a different MCP server... file it with that server instead'). Also instructs not to paste end-user prompts, and explains the claim_token workflow for follow-up.

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

A4/5.0
Disambiguation4/5

Most tools target a distinct action or resource, and the long routing descriptions make choices like ask_pipeworx vs ask_pipeworx_grounded vs deep_research clear. The main weak spots are ask_pipeworx_beta being currently identical to ask_pipeworx and the six overlapping Polymarket tools, but each has a discernible workflow.

Naming Consistency3/5

Naming has internally consistent subfamilies such as censtatd_*, ask_pipeworx*, and polymarket_*, but overall it mixes verb-first names (get_table, validate_claim, subscribe), noun-first names (entity_profile, bet_research, pipeworx_feedback), and bare imperatives (remember, forget, recall). The set is readable but does not follow one convention.

Tool Count2/5

35 tools exceeds the 25+ threshold and feels heavy, especially since many tools (generate_llms_txt, scan_dependency, pipeworx_feedback, pipeworx_trending) are unrelated to the HK Census core implied by the server name. The broad Pipeworx scope explains the width, but the surface is still large for an agent to navigate efficiently.

Completeness4/5

For a read-only research/data-access gateway, coverage is strong: generic lookup, grounded verification, deep research, entity profile/compare/change, entity resolution, memory, and subscription lifecycle are all represented. Minor gaps exist, such as no subscription update, no explicit bulk/export path, and fewer HK C&SD convenience wrappers, but agents can work around them.

Resources