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Synapse Layer — Trust Infrastructure for AI Agents

list_memories

Read-only

List memory metadata with pagination and governance limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum memory metadata rows to return. Hard-capped: default 5, max 10. Values above 10 are silently reduced to 10.
scopeNoExplicit memory scope. "agent" (default, fail-closed) = lists memories for the given agent_id (or the token agent). "tenant" = lists memories across all agents of the authenticated tenant.
subjectNoESCOPO1 (optional): opaque 8-128 char token ([A-Za-z0-9._:-]) that isolates memory to a single person within a shared connect-token. Omit for token-scoped behavior. Never include PII/email.
agent_idNoAgent identifier (canonical or alias). Used only when scope="agent" or scope is inferred.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
totalNo
memoriesYes

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered without description credit. The description adds 'pagination and governance limits,' which hints at bounded output and scope-based restrictions beyond the annotation. However, the concrete behaviors (hard cap of 10, silent reduction, fail-closed scope default) live in the schema, not the description.

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?

A single seven-word sentence with zero waste. The core action and resource are front-loaded, followed by the two governing concepts (pagination, governance limits). Every word earns its place.

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

Completeness3/5

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

The presence of an output schema means return values need no description, and the fully detailed schema plus readOnly annotation carry most of the burden. The notable gap is routing: with 12 memory-flavored siblings, the description doesn't help an agent decide when listing metadata is the right operation versus retrieving content via recall or search.

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 the baseline is 3 even with no param info in the description. The terms 'pagination' and 'governance limits' loosely map to the limit and scope parameters but add little meaning beyond what the schema already states in greater detail (hard caps, silent reduction, fail-closed behavior, PII warning).

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 pairs a specific verb (List) with a specific resource (memory metadata), and the 'metadata' qualifier implies enumeration of records rather than content retrieval, which loosely distinguishes it from content-returning siblings like recall and search. However, it doesn't explicitly differentiate from the several memory-related siblings (recall_memory, search, store_memory), leaving some inference required.

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?

The description provides no guidance on when to use this tool versus alternatives. With 12 siblings — including recall, recall_memory, search, save_memory, and store_memory — there is real routing risk and nothing in the description mitigates it. The schema's scope parameter details are functional semantics, not usage direction.

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

B3.1/5.0
Disambiguation2/5

Several tools are redundant: recall_memory is explicitly an alias of recall, and save_memory/save_to_synapse/store_memory all persist memories. This makes the tool boundary unclear for agents choosing between them, even though core operations like health_check and slo_report are distinct.

Naming Consistency2/5

Names are consistently snake_case, but verb usage is inconsistent: save_memory, save_to_synapse, and store_memory use different verbs for the same operation, and recall/recall_memory add an alias rather than following one convention. The pattern is readable but not predictable.

Tool Count3/5

Thirteen tools is not inherently excessive for an agent-memory/trust service, but the presence of multiple aliases inflates the surface and means not every tool earns its place. The effective set is smaller, making the count feel padded.

Completeness3/5

The surface covers initialization, save, list, search/recall, feedback, and handover, but there is no update or delete operation for memories. This leaves lifecycle management incomplete and may force agents to work around missing state-management operations.