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Censtatd Hk

by io.github.pipeworx-io

Censtatd Get Table

censtatd_get_table
Read-onlyIdempotent

Fetch a Hong Kong Census & Statistics Department statistical table as structured JSON (time series of {period, sv (measure), svDesc, figure} plus any dimension code/Desc columns). By default returns the FULL series (full_series=1) — reliable and keyless, no encoded param needed. Use this for HK GDP, employment earnings, trade, prices, money/financial-market stats, etc. Table ids look like '310-31001' (GDP) or '340-46001' (exchange rates); find ids with censtatd_search_tables. Optionally pass param — the opaque lz-string blob copied from the table's API Example box on censtatd.gov.hk — to fetch a filtered subset instead of the full series (we cannot generate this blob for you).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTable id, e.g. '310-31001' (GDP), '340-46001' (exchange rates).
langNoDescription language: en, tc (traditional), sc (simplified). Default en.
paramNoOPTIONAL opaque lz-string param copied from the C&SD web_table "API Example" box. When provided, full_series is disabled and only the encoded selection is returned. Cannot be hand-constructed; omit it to get the full series.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds context about default full-series return (full_series=1), reliability, keyless access, and the opaque param's behavior. No contradictions.

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?

Exceptionally concise: three focused sentences covering purpose, usage context, and param caution. Every sentence adds value without 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?

Given no output schema, the description fully explains the return format (time series with specific columns). Parameter descriptions are complete, and it references the sibling for ID lookup. The tool is self-contained and clear.

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%, and the description enriches each parameter: 'id' with examples, 'lang' with enum values, 'param' with detailed usage notes and constraints. Exceeds mere schema replication.

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 specifies a clear verb ('Fetch') and resource ('Hong Kong Census & Statistics Department statistical table'), details the output format (structured JSON with time series columns), and distinguishes itself from sibling 'censtatd_search_tables' by guiding users to find table IDs there.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit use cases ('HK GDP, employment earnings, trade, prices') and directs to sibling for ID discovery. Does not explicitly state when to avoid using this tool, but context is sufficient for most agents.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Censtatd Hk toolsInspect
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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