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find_example

Search verified, framework-specific code examples by task, language, framework, or target API to solve coding implementation questions.

Instructions

Find verified, framework-specific code examples by task, language, framework, or target API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of examples to return (default: 5).
queryYesImplementation task or symbol to look for examples of (e.g. "verify webhook signature", "constructEvent").
formatNoResponse format: "markdown" (default, human/agent-readable documentation) or "json" (structured raw machine data).
versionNoTarget documentation version filter.
languageNoProgramming language filter (e.g. "typescript", "python", "go").
frameworkNoFramework filter (e.g. "express", "fastapi", "next").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.3
    • addedInput schema / properties / format
      Added value: +{
+  "description": "Response format: \"markdown\" (default, human/agent-readable documentation) or \"json\" (structured raw machine data).",
+  "enum": [
+    "markdown",
+    "json"
+  ],
+  "type": "string"
+}
  2. First observedv0.1.4

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden. It asserts examples are 'verified' (a useful quality signal) but says nothing about permissions, rate limits, freshness, or what 'verified' actually means; return shape is only inferable from the format param.

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?

A single well-formed sentence front-loads the verb, the resource, and the qualification 'verified, framework-specific'. Nothing is wasted and nothing is buried.

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?

For a 6-parameter search tool with no output schema and no annotations, the description covers purpose but omits result behavior, ranking/relevance expectations, and sibling routing. It is minimally viable rather than complete.

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 all six parameters are already documented, including the format enum, limit default, and filter examples. The description's phrase 'by task, language, framework, or target API' loosely mirrors those params but adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

The description gives a specific verb (Find) and resource (verified, framework-specific code examples) plus the scoping axes (task, language, framework, target API). This clearly distinguishes it from content-oriented siblings like search_docs or find_recipe, though it never names an alternative directly.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can infer it should call this when it needs a code example rather than prose docs. There is no explicit 'use this when' statement, no mention of when NOT to use it, and no routing to find_recipe/find_api despite those close siblings.

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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