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memory_search

Find specific text in your hierarchical markdown memory system by searching across rooms or a sub-path.

Instructions

Full-text search across the palace (or a sub-path).

Uses ripgrep (rg) if available; falls back to Python re. Returns up to 20 matches, each showing the relative file path, line number, and matched line with 1 line of context on each side.

path narrows the search to a specific room or subdirectory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations exist, so the description carries full burden. It discloses implementation (ripgrep vs. Python re), result limit of 20 matches, output structure (path, line number, line, context), and use of path parameter for scope. Missing details like authorization or performance, but overall strong.

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 concise, front-loads the purpose, and every sentence contributes useful information without redundancy. It efficiently covers implementation, limits, parameters, and output format in a short paragraph.

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 the presence of an output schema (context signal) and the tool's complexity, the description covers core functionality, implementation, limits, and parameter effects. It omits explanation of the 'palace' metaphor and result ordering, but overall is sufficient for an AI agent to use correctly.

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?

With 0% schema description coverage, the description must compensate. It clarifies that 'query' is a search term (implied regex) and 'path' narrows to a subdirectory. This adds meaning but could be more specific about query syntax and behavior when omitted.

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 performs full-text search across the palace (or sub-path), specifying the search engine used and result limits. This distinguishes it from sibling tools like memory_list or memory_read which are not search-oriented.

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

Usage Guidelines2/5

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

The description does not explicitly advise when to use this tool versus alternatives. It only hints at narrowing search via the path parameter but lacks explicit 'when-to-use' or 'when-not-to-use' guidance, nor does it mention sibling 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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