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Hnb Hr

by io.github.pipeworx-io

Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, ensuring the agent knows it's a safe, idempotent read operation. The description adds behavioral context: fetches the page, extracts title/description/key links, and emits standard markdown format, which goes beyond 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?

The description is two sentences plus a bullet list, front-loaded with the main purpose. Every sentence earns its place with no wasted words.

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 specifies output as a single text blob in standard markdown format. Combined with annotations for safety, the description fully covers what the tool does and produces.

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 description coverage is 100%, so baseline is 3. The description adds marginal value with an example URL format and mentions the output format, but parameter details are already in the schema.

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 it generates a production-ready llms.txt file for any URL, specifying the verb (generate), resource (llms.txt file), and purpose for AI crawlers. It distinguishes from sibling tools like ai_visibility_check and scan_competitor_ai_presence by focusing on file generation rather than visibility scanning.

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?

The description lists explicit use cases: getting a client's site indexed, drafting for own project, or auditing competitor. It provides clear context for when to use the tool, though it does not explicitly state when not to use it or mention alternatives.

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

A3.7/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (beta is currently identical to ask_pipeworx), and deep_research and validate_claim also overlap with the ask_pipeworx family. The Polymarket tools are more distinct, but the query family creates real ambiguity.

Naming Consistency2/5

Tool names mix leading verbs (ask_, compare_, resolve_, scan_) with leading nouns (entity_profile, recent_changes, hnb_currency_rate) and there are multiple subfamily prefixes (ask_pipeworx_*, polymarket_*, hnb_*). All are snake_case, but no consistent verb_noun or noun pattern is followed.

Tool Count2/5

33 tools is well above the 25+ threshold, and the server name ('Hnb Hr') implies a narrow Croatian banking scope while the majority of tools are for a broad data research platform. Many meta-tools (discover_tools, suggest_questions, pipeworx_feedback, pipeworx_trending) inflate the count beyond what the apparent purpose needs.

Completeness3/5

The HNB currency functionality is complete (single and all rates, historical and latest), and the broader data platform offers good coverage via the ask_pipeworx router, subscriptions, and memory tools. However, there are gaps (no direct HNB news or historical archive tool, patents soft-fail, and out-of-domain tools like generate_llms_txt), and the mismatch between server name and content leaves the surface feeling incomplete.

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