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Configure Memory

configure_profile_search

Read-only

Search or list permitted attributed profile memories/facts for the current user. Use this for personalized help, targeted retrieval, source-specific questions, or exact memory/fact lookup. For personalized help, pass a concrete query about the current task and relevant filters when known; no overview is needed first. Omit query or pass "" only when the user asks to list saved memories, narrowing by the requested source, category or date when specified. For "what does know about me?", pass query "" plus source, e.g. "tempo" or "chatgpt". To search inside one category from configure_profile_read's table of contents, pass box with that box id, e.g. "work"; box narrows to the settled category facts and composes with query. For relative-date questions, resolve dates first and pass from/to; compact results may include snippets. Pass detail "full" when complete result text or inspectable metadata matters. Results from an import also carry imported_by_agent and import_id, which is what configure_profile_forget takes to retract that whole import.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoOptional inclusive end date filter in YYYY-MM-DD format for date-attributed results.
boxNoOptional category box id from configure_profile_read's table of contents, such as "work". Filters to the settled facts in that box and composes with query; unknown or empty boxes return empty results, never an error.
fromNoOptional inclusive start date filter in YYYY-MM-DD format for date-attributed results.
limitNoOptional maximum result count. The backend enforces a default and hard cap.
queryNoOptional search query. Omit or use "*" to list bounded permitted attributed profile results, for example with a source filter.
detailNoOptional result detail. Defaults to compact, which truncates long memory text. Full returns the complete text plus markers. Every result at either detail carries id, source, written_by, and saved_on (a YYYY-MM-DD date that matches the from/to filters).
sourceNoOptional explicit source handle filter, such as "tempo", "chatgpt", or "import:chatgpt". Source-box ids from configure_profile_read's table of contents ("agents/<name>", "imports/<provider>") are also accepted and mean the same source. This is not a path or connector and there is no magic self value.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesMatching attributed memories, each with id, text and source.
guidanceNoWhat to do next when results are thin: a status, a short explanation, and a suggested next action.
visibleSourcesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: unknown/empty boxes return empty results rather than errors, the backend enforces a default and hard cap on limit, compact truncates long text while full returns complete text plus markers, and import results carry imported_by_agent/import_id. It stops short of a fully rich operational picture (e.g. ordering, pagination), so 4 rather than 5.

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?

Front-loaded with purpose and then organized by use case, with each sentence carrying actionable routing or parameter guidance. It is dense but not padded; the trailing sentence about configure_profile_forget's import retraction is slightly tangential yet still useful cross-tool context.

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

Completeness5/5

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

An output schema exists, so return-value detail needn't be restated, and annotations cover the safety profile. Between the description, 100% schema coverage, and the output schema, an agent has everything needed to call this correctly across the described scenarios.

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 100%, so the baseline is 3. The description nonetheless adds non-obvious usage semantics: pass '*' with a source for source-scoped questions, box composes with query, resolve relative dates before passing from/to, and detail 'full' when complete text or metadata matters. It clarifies intent beyond the schema's field definitions.

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?

States a specific verb and resource ('Search or list permitted attributed profile memories/facts for the current user') and immediately scopes it against siblings by referencing configure_profile_read's table of contents and configure_profile_forget's import id. An agent can distinguish this from the other configure_profile_* tools without opening schemas.

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

Usage Guidelines5/5

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

Explicitly enumerates when to use it: personalized help, targeted retrieval, source-specific questions, exact lookup, listing, and relative-date questions. It also names the alternative (configure_profile_read for the table of contents) and gives concrete call recipes such as query '*' plus source for 'what does <source> know about me?'.

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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