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MockHero

by io.github.dinosaur24

estimate_agent_usage

Estimate MockHero agent-plan cost before generating data. No login or API key is required; include an API key only when you want the estimate to use actual daily usage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoSeed for reproducible output.
scaleNoMultiplier for template record counts.
formatNojson
localeNoDefault locale such as en, de, fr, es, or ja.
promptNoPlain-English data request. Example: 50 users and 200 orders linked to them.
tablesNo
api_keyNoOptional MockHero API key for no-auth MCP clients. Prefer the Authorization header when the client supports it.
templateNo
sql_dialectNo
daily_used_beforeNoOptional assumption when no API key is supplied.
estimated_recordsNoRequired for prompt estimates because this tool does not run prompt-to-schema conversion.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior4/5

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

Annotations are minimal (all false), so the description carries the burden. It discloses that no login/API key is required and explains the optional API key's effect on using actual daily usage, which adds useful behavioral context beyond annotations. It stops short of describing side-effect behavior fully, but the 'before generating data' implies no data mutation.

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?

Two sentences, front-loaded with purpose and immediately useful behavioral details. No wasted words or redundant schema repetition.

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

Completeness3/5

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

While the output schema covers return values, the description does not explain the different estimation modes (tables/template/prompt) or clarify how parameters like estimated_records are required for prompt-based estimates. Given the tool's complexity (11 params, three anyOf variants), this is a notable gap even with schema annotations.

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 64%, so baseline 3 is appropriate. The description does not explain the three estimation modes (tables, template, prompt) or which parameters to use for each, leaving the anyOf structure in the schema to carry that burden. The description adds no direct parameter-level information.

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 states 'Estimate MockHero agent-plan cost before generating data' with a clear verb and resource, and distinguishes it from sibling tools like generate_test_data and generate_from_template by focusing on cost estimation rather than data generation.

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 phrase 'before generating data' implies temporal context, and the note about when to include an API key provides decision guidance. However, it does not explicitly name alternative tools or state when not to use this tool, so it isn't a full 5.

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

A4.1/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose. generate_test_data and generate_from_template could overlap, but descriptions distinguish custom/plain-English generation from pre-built templates. The payment lifecycle tools (create_agent_checkout, check_agent_checkout_status, claim_agent_api_key) are sequential and clearly scoped.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (e.g., create_agent_checkout, list_field_types, generate_test_data). generate_from_template uses verb_preposition_noun but remains in the same style. No mixing of conventions.

Tool Count5/5

9 tools is well-scoped for a test data generation service with monetization. Each tool earns its place, covering data generation, schema discovery, and payment flow without redundancy or bloat.

Completeness4/5

The tool set covers the core generation workflows, schema construction, and the full checkout-to-key-claim lifecycle. Minor gaps exist, such as no API key management (e.g., revoke or refresh) and no template customization, but these are not critical for the primary use case.

Resources