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jmjava
by jmjava

search_memory

Find past project decisions, session notes, and state by querying local Markdown memory. Filter by project and control result count.

Instructions

Search project state, sessions, and decisions with local text matching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Local text matching' is a genuine behavioral trait, indicating that search is text-based rather than semantic or remote, but the description does not mention result ordering, read-only behavior, or limitations.

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 a single, front-loaded sentence with no filler. It communicates the core action, scope, and mechanism efficiently in nine words.

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 straightforward search tool, the core purpose and mechanism are present, and an output schema exists to cover return values. However, the lack of usage guidance and parameter semantics leaves the definition minimally viable rather than complete, especially given the absence of annotations.

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 needed to explain the roles of query, limit, and project. It does not; the tool purpose only loosely implies the query parameter, while limit and project remain entirely undocumented in the description.

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 clearly states the action ('Search') and the resource scope ('project state, sessions, and decisions'), which is specific enough to distinguish it from generic memory tools. It also adds the mechanism 'local text matching' for extra clarity, though it does not explicitly compare against sibling tools like read_note or get_project_context.

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?

There is no guidance about when to use this tool versus its siblings, such as get_project_context or read_note, and no exclusions or alternative recommendations. The intended use is only implied by the name and description, leaving the agent to infer the appropriate context.

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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