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Synapse Layer — Trust Infrastructure for AI Agents

neural_handover

Transfer contextual state between agents with continuity controls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesThe handover token (64 hex chars). Generated by the source agent/user in Forge UI.
reasonYesREQUIRED (10–200 chars). Human-readable justification for consuming this handover. Example: "Receiving project context from Claude session."
consuming_agentNoAgent identifier consuming the handover (defaults to token agent).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
handoverIdNo

TDQS

B3.3/5.0
Behavior3/5

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

Annotations show readOnlyHint=false (mutable) and openWorldHint=false (bounded), but the description doesn't disclose what continuity controls entail, whether the handover is destructive to the source, or if auth tokens are required. Output schema exists but description adds no behavioral detail beyond the schema's token/reason requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence, front-loaded with key action. However, key details like the required token and reason are only in the schema, and continuity controls are vague—could be expanded without bloat to be more helpful.

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?

With an output schema present, return values don't need explanation. However, given the complexity of state transfer semantics and no mention of side effects or continuity control specifics, the description feels incomplete for agents needing to understand impact before invocation.

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 schema already documents all three parameters with descriptions. The description explicitly mentions token and reason but adds no extra meaning like format constraints or examples beyond what the schema provides. Baseline 3 is appropriate.

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 states it transfers contextual state between agents with continuity controls, specifying verb and resource. It distinguishes from sibling tools like initialize_context or process_text by focusing on state transfer rather than initialization or processing.

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 use when handing off context between agents but does not explicitly state when-not-to-use or exclude alternatives like initialize_context for fresh starts. No guidance on preconditions or when a handover is inadvisable.

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.