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rafalswiderski

Dynamic Code Executor MCP Server

search_cached_scripts

Search previously executed scripts semantically to reuse working solutions. Find code that solves similar problems, even if exact code differs.

Instructions

Search for similar cached scripts using semantic search.

Finds previously executed scripts that solve similar problems, even if the exact code differs. Use this when you need to solve a task - there might already be a working solution cached.

Example queries:

  • "fetch data from REST API"

  • "parse JSON and extract fields"

  • "read CSV file and calculate sum"

  • "scrape webpage content"

Returns ranked results by similarity with scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (default: 10)
queryYesDescription of what you want to do
languageNoFilter by language (optional)
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that results are ranked by similarity with scores, and that it performs semantic search over cached scripts. This goes beyond the schema and provides meaningful behavioral context, though it does not mention potential limitations like scope of the cache.

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?

The description is well-structured with a concise opening, a usage note, and relevant example queries. Every sentence contributes value, and the bulleted examples improve clarity without bloating the text.

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?

Given there is no output schema, the description adequately covers the return format ('ranked results by similarity with scores') and the tool's purpose. It is complete enough for a search tool, though it could mention how limit and language affect behavior, but the schema already covers those.

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 the baseline is 3. The description adds example queries to illustrate the 'query' parameter but does not enrich the meaning of 'limit' or 'language' beyond their schema definitions.

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 uses the specific verb 'search' and clearly identifies the resource ('cached scripts') and method ('semantic search'). It states it finds previously executed scripts solving similar problems, distinguishing it from siblings like list_cached_scripts (which likely lists all) and get_cached_script (which retrieves a specific one).

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?

It gives explicit usage context: 'Use this when you need to solve a task - there might already be a working solution cached.' This tells the agent when to invoke the tool, though it doesn't provide when-not conditions or explicitly name alternative 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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