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PublicAPIs.io

get_quickstart

Read-only

Ready-to-run example code for calling an API, in javascript, python or curl. Use when you are about to integrate an API into code. Verified samples are marked verified=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
languageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read. The description adds that samples carry a verified flag, which is genuinely useful beyond the annotation, but says nothing about what happens when no sample exists for a language or whether the slug must refer to an existing API.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with what the tool returns, followed by the usage trigger. No filler, though the trailing verified=true note is slightly tacked on rather than integrated.

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?

There is no output schema, so the description reasonably omits return-value detail, and the read-only annotation covers safety. However, the tool's sole required parameter (slug) is left semantically unexplained, which is a real gap for an agent trying to invoke it correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter meaning. It restates the language enum values (javascript, python, curl) that the schema already declares, and only hints that 'slug' identifies an API — it never explains the slug format, whether language is optional, or the default behavior.

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?

States a specific verb+resource: it returns ready-to-run example code for calling an API, in one of three languages. This is distinguishable from siblings like get_api (metadata) or search_apis (discovery), though no sibling is named explicitly.

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?

"Use when you are about to integrate an API into code" gives a clear triggering context. It does not name alternatives (e.g., use get_api first to find the slug) or state exclusions, so it stops short of a 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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