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HSH Data-on-Demand

by io.github.hshintelligence

hsh-b2b-contact

Verified B2B contact records: name + business email + company. SMTP-validated emails (bounce rate <3%). Industry/title filters. Per-record pricing scales with quantity. Tier 1: 1-50 records ($3-15). Tier 2: 51-5000 records ($15-500). Tier 3: 5001-100K ($250-3000).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleNoJob title or role (e.g., 'CTO', 'Founder', 'Head of Marketing').
industryNoIndustry filter (e.g., 'D2C skincare', 'B2B SaaS').
locationNoCity, state, or country.
quantityYesNumber of contacts needed (1-100000).

TDQS

A3.6/5.0
Behavior4/5

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

Given no annotations, the description provides good behavioral context: SMTP-validated emails, bounce rate <3%, and per-record pricing with quantity tiers. It does not cover latency, rate limits, or authorization, but overall is sufficient.

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?

Description is brief and front-loaded with key information: what the tool provides, quality assurance, filters, and pricing. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 parameters and no output schema, the description covers core functionality, data quality, filters, and pricing. However, it does not specify the return format (e.g., array of objects), which would be helpful.

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% (all parameters described in schema). The description does not add additional meaning to individual parameters beyond what the schema provides, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool provides verified B2B contact records with name, business email, company, and mentions SMTP validation and pricing. However, it does not explicitly differentiate from sibling tools like hsh-b2b-enriched or hsh-b2b-full.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. The description mentions pricing tiers and filters but does not advise on context or exclusions for using this over other B2B tools.

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
Disambiguation4/5

Most tools have distinct purposes, but some closely related tools (e.g., hsh-b2b-*, hsh-esg-* variants) could cause confusion. Descriptions help differentiate, but an agent might still misselect similar products.

Naming Consistency3/5

Naming convention is mixed: some tools use hyphens (hsh-b2b-contact), others use underscores (hsh_broker_data_request). While mostly readable, the inconsistency could be confusing for agents expecting a uniform pattern.

Tool Count3/5

32 tools is on the high side for a single server, but given its purpose as a data marketplace, the large number reflects a wide catalog. However, it may be overwhelming for agents to navigate.

Completeness3/5

Covers many data domains but has obvious gaps (e.g., weather, social media). The inclusion of custom data request tools (hsh_describe_data_need, hsh_broker_data_request) mitigates these gaps, allowing agents to request missing data.

Resources