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search_memory

Search long-term memory by keyword to recall past decisions, findings, and notes from structured memory and journal files.

Instructions

Search the memory palace by keyword.

Looks across Metis's long-term memory to recall past context — what was
decided, found, or noted before. It searches the memory_entries table
(title, summary, topics) and also greps journal/**/*.md files on disk, so
both structured memory and freeform journal notes are covered.

Args:
    query: Keyword or phrase to match against entry titles, summaries,
        topics, and journal note text.
    entry_type: Optional filter limiting results to one kind of entry —
        "session", "journal", "idea", "decision", or "topic". Empty string
        (default) searches all types.

Returns:
    A text block of matching memory entries and journal hits, or a message
    when nothing matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
entry_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and discloses that it searches both a database table (memory_entries) and journal files on disk. It mentions the specific fields searched (title, summary, topics) and the method (grep). This gives good insight into the tool's behavior.

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?

The description is about 150 words, well-structured with a clear opening sentence, explanatory paragraph, and explicit Args/Returns sections. It is front-loaded and efficient, though could slightly trim the Returns section.

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 simplicity (2 params, no enums, output schema exists), the description covers what it does, how to use it, and what to expect in return. It mentions handling of empty results. It is complete enough for an agent to invoke correctly.

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 has 0% description coverage. The description adds an 'Args' section explaining both parameters: 'query' as a keyword/phrase to match, and 'entry_type' as an optional filter with listed possible values. This provides meaning beyond the schema's basic titles.

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 identifies the action (search) and resource (memory palace / long-term memory). It explains what kind of context is recalled. However, it does not explicitly distinguish this tool from sibling search tools like search_session_memory or search_library.

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

Usage Guidelines3/5

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

The description implies usage for recalling past context from long-term memory, but it does not specify when to use this tool instead of alternatives like search_session_memory or search_notes. No exclusion criteria are provided.

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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