Skip to main content
Glama

search_session_memory

Search past session summaries to recall what was discussed, such as decisions made or actions taken. Retrieve relevant results by entering a keyword or phrase.

Instructions

Search past session summaries for a topic or keyword.

Use this to recall what was discussed in previous sessions — e.g.
"what did we decide about the installer?" or "when did we build APScheduler?".

Args:
    query: Keyword or phrase to search for.
    limit: Maximum number of results to return (default 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden but only states that it searches past session summaries. It does not disclose behavior like whether it searches all sessions or only summaries, permission requirements, or result format. The read-only nature is implied but not explicit.

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 extremely concise with a single opening sentence followed by a usage hint and example queries. Every sentence adds value, and the parameter descriptions are compact yet informative. No fluff.

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 tool's low complexity, the description covers the core functionality and parameter semantics. An output schema exists, so return values need not be described. However, additional context about how this differs from sibling 'search_memory' could enhance completeness.

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?

Schema description coverage is 0%, so the description compensates by explaining 'query' as 'Keyword or phrase to search for' and 'limit' as 'Maximum number of results to return (default 10)'. This adds meaningful context beyond the bare schema.

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 'Search past session summaries for a topic or keyword' with specific verb and resource. It distinguishes itself from sibling tools like 'search_memory' by specifying 'session summaries' and provides concrete example queries.

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?

The description explicitly says 'Use this to recall what was discussed in previous sessions' with example queries, giving clear context. However, it does not provide exclusion criteria or explicitly differentiate from similar tools like search_memory.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SVerITG/Metis_PH'

If you have feedback or need assistance with the MCP directory API, please join our Discord server