memoket

list_conversations

Read-only

[metadata_query] List recordings by time window / participants. Returns id, title, started_at, ended_at, duration_seconds, participants, language_code (no content). Paginated (count default 100, max 200; offset). order_by ranks within the window. NOTE: participants are speaker labels — placeholders ('Speaker A/B') unless the user tagged them, not necessarily real names.

Input Schema

TableJSON Schema

Name	Required	Description
`desc`	No	true = descending (default); false = ascending.
`count`	No	page size (default 100, max 200)
`offset`	No	page offset; use the response's next_offset
`end_time`	No	ISO 8601, filters on started_at
`order_by`	No	duration_seconds \| started_at \| action_item_count — server sorts the whole window and returns the top `count`.
`start_time`	No	ISO 8601, filters on started_at
`participant_names`	No	Exact participant filter (may return 0 for un-tagged/anonymized people).

Output Schema

TableJSON Schema

Name	Required	Description
`tool`	Yes
`result`	Yes	Tool-specific result payload; shape varies per tool (object for most; may be null/array/text for some). Intentionally type-unconstrained for strict-validating clients.
`took_ms`	No

TDQS

A4.7/5.0

Behavior5/5

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

Adds significant behavioral context beyond annotations: pagination limits, ordering behavior, participant name caveat. No contradictions with annotations.

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?

Two focused sentences plus a note; every sentence adds value. Front-loaded with core purpose.

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?

Covers pagination, ordering, participant caveat, and return fields. Output schema handles detailed return structure. Fully meets complexity of 7 parameters.

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 coverage is 100%, but the description adds meaning for order_by (whole-window sorting) and participant_names (exact filter, potential empty results).

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 'List recordings by time window / participants' and specifies returned metadata fields, distinguishing it from content-focused siblings like get_transcripts.

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?

Provides context on filtering by time/participants, pagination, and a note on speaker labels, but lacks explicit when-not-to-use or alternative sibling references.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct aspect: metadata, content types (brief, summary, transcript), filtered transcript, listing, and search. No two tools overlap in purpose.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern using snake_case (get_*, list_*, search_*), making their actions predictable.

Tool Count5/5

Seven tools cover the retrieval scope without being too many or too few; each serves a clear function in the conversation management domain.

Completeness3/5

The server lacks direct fetchers for several result types from search (e.g., memory_atoms, segments, action_items), creating dead ends for agents that need to retrieve those details.

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