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ykovenskiy-hub

Purl MCP Server

search_scripts

Find every occurrence of a substring across all scripts in a Purl project, returning the target, script name, line number, and matching line. Use it to locate where a variable or function is referenced before editing.

Instructions

Search every script in the project (all cell-script tabs and all object-level scripts, templates included) for a substring. Returns one entry per matching line with target/scriptName/lineNumber/line so the result is directly actionable. Pass contextLines: N to also return the N lines above and below each match — usually enough to skip a follow-up get_script call. Use this whenever you need to answer "where is X used / set / played / spawned / destroyed / handled" before making changes — the only reliable way to enumerate distributed Purl logic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSubstring to find. Case-sensitive by default; pass caseInsensitive: true to relax.
cellNameNoOptional: restrict search to a single cell (by label). Default searches all cells.
contextLinesNoOptional: number of lines of context to include above and below each match (returned as contextBefore / contextAfter arrays on each match). Default 0 (no context). Capped at 20.
caseInsensitiveNoOptional: when true, match case-insensitively. Default false.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the return structure, contextLines behavior with default and cap, and case sensitivity option. It does not mention potential performance issues or what happens when no matches are found, but core behavior is well covered.

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?

Three sentences, front-loaded with purpose, followed by return format and usage guidance. Every sentence earns its place with no redundancy or fluff.

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

Completeness5/5

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

For a search tool with no output schema, it provides a complete picture: scope (all scripts including templates), return fields, contextLines option, and case sensitivity. It also gives usage context, making it sufficient for an agent to decide when and how to invoke the tool.

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

Parameters4/5

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

The schema covers 100% of parameters, so baseline is 3. The description adds value by explaining the practical benefit of contextLines ('usually enough to skip a follow-up get_script call') and reiterates the scope of the search, going beyond simple schema repetition.

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 states 'Search every script in the project... for a substring' with a specific verb, resource, and scope, clearly distinguishing it from siblings like get_script or read_project_scripts. It also specifies the output format ('target/scriptName/lineNumber/line'), making the purpose unambiguous.

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

Usage Guidelines5/5

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

It explicitly says 'Use this whenever you need to answer "where is X used..." before making changes', giving a clear when-to-use directive. It also mentions skipping a follow-up get_script call, providing a practical alternative comparison.

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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