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Glama

Companies House

by io.github.pipeworx-io

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: data source ('CF analytics-engine'), no PII, caching behavior (5min-1h), and the aggregated nature ('just (pack, tool, count)'). No contradictions with 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?

Four sentences, no wasted words. First sentence states purpose, second lists use cases, third clarifies data origin and privacy, fourth mentions caching. Information is front-loaded and easy to parse.

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 no output schema, the description sufficiently explains what is returned (top tools, packs, call volume) and adds caching details. For a simple, read-only tool with no required parameters, this is complete and actionable.

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

Parameters5/5

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

Schema covers the single parameter 'window' with enum and description. The description adds semantic guidance: 'Shorter windows surface what's hot right now; longer windows show steady-state demand,' helping the agent choose based on intent. With 100% schema coverage, this baseline is 3, but the additional context justifies a 5.

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?

Description clearly states the resource ('top tools, top packs, and total call volume') and the action ('Returns'), making the tool's function immediately obvious. It is easily distinguishable from sibling tools like ask_pipeworx or discover_tools by focusing on trending usage rather than direct queries or general discovery.

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?

Three specific use cases (discovering hot data sources, confirming popular tools, seeing alignment with agent needs) provide clear context for when to use this tool. However, it does not explicitly mention when not to use it or compare it to alternatives like discover_tools, which could further guide agent decision-making.

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.

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