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Zambo

Credithunt

credithunt
Read-onlyIdempotent

Live verified index of AI and cloud startup credit programs. Accepts an optional technology stack and stage. Returns matching programs, eligibility details, current links, and available credit information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stackNoYour tech stack for matched recommendations. Example: ["openai","vercel","aws"]. Leave empty to get all programs.
stageNoYour stage: solo (1 person), early (2–10), growth (10+). Default: solo.
min_valueNoMinimum credit value in USD to filter by (optional). Example: 5000

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
matchedNo
programsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side-effect profile. The description adds that the index is 'live' and 'verified' and enumerates the output fields (eligibility details, current links, credit info), which goes beyond the annotations. 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?

Two sentences with no redundant words. The core purpose and inputs are front-loaded, and the output components are listed efficiently. Every clause adds value.

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?

The description states inputs (optional stack/stage) and outputs (programs, eligibility, links, credit info). The presence of an output schema covers return details, and all parameters are documented. The tool is simple and well-scoped; nothing critical is missing for correct invocation.

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?

The input schema provides full descriptions for all three parameters (stack, stage, min_value), so schema coverage is 100%. The description only repeats that it accepts an optional stack and stage without adding new semantics, formats, or relationships. Baseline 3 applies because the schema does the heavy lifting.

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 the tool provides a 'live verified index of AI and cloud startup credit programs' and accepts optional stack and stage inputs. It is specific about the resource (credit programs) and the action (retrieval/filtering), and it stands apart from unrelated sibling tools.

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 implies usage when an agent needs matching startup credit programs and indicates optional filters. It does not explicitly list exclusions or alternatives, but none are needed given the unrelated sibling set. The context is clear enough for an agent to decide when to call it.

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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