Skip to main content
Glama

trawl_memory_search

Search stored memories semantically to retrieve relevant context by query, optionally filtering by namespace or memory pool.

Instructions

Search stored memories semantically.

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query
top_kNoNumber of results (default: 5)
namespaceNoFilter by namespace
pool_nameNoPool scope (optional, global if omitted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.4.1

TDQS

C2.9/5.0
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, yet it only says the search is semantic. It omits ranking/ordering behavior, default result count behavior, what happens when namespace or pool_name are omitted, whether results span pools, and whether the operation is read-only or touches state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero filler or repetition. It is efficient, but the brevity crosses into under-specification for a four-parameter tool with no annotations.

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

Completeness2/5

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

With four parameters, no annotations, and no output schema, the description should explain the memory/pool/namespace model and how results are ordered, but it does none of that. An agent can form the call from the schema but cannot predict what it will get back or how scoping interacts.

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 four parameters (query, top_k, namespace, pool_name) are already documented in the schema. The description adds only the word 'semantically', which implies the query is matched by embedding similarity rather than keywords — a small but real signal beyond the schema.

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?

States a specific verb (search) and resource (stored memories) plus the retrieval mode (semantically), so the agent knows this is semantic retrieval over the memory store rather than code or graph search. It does not distinguish itself from neighbors like trawl_memory_list, trawl_search, or trawl_search_pool, so an agent must infer the boundary.

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 when-to-use guidance at all: nothing says whether to reach for this versus trawl_memory_list (enumeration) or the generic trawl_search, and no prerequisites or exclusions are given. The agent has to guess based on the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.