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mcp_engram_turn_record

Record an agent response turn with user utterance, assistant output, and auto-aggregated trace data to maintain conversation history.

Instructions

Mint an RPT v3 agent_response turn tile (response_tile_schema_v3). Captures user utterance + assistant output + auto-aggregated trace_chain/probe_reads/tool_calls from activity feed. Use at end of each assistant turn (lean default). Extends prior strange-loop RPT v2 convention to all chat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_thesisNo
assistant_outputYesFinal user-visible assistant reply (excerpt ok)
conv_arcNoConversation arc id e.g. conv:leg-rpt-v3
goal_contextNoGoal this turn serves
human_forwardYesLeading plain-language thesis — what happened and why it matters
open_questionsNo
outcome_statusNocompleted | partial | blocked | needs_user
prev_turnNoPrior tile:agent_response_* for turn chaining
process_contextNoOptional process:engram.* — realized_by edge
since_tsNoActivity window start (ms since epoch). Default: last 10 minutes.
spatial_touchedNo
tierNolean (default) | full (strange-loop/meta with key_facts)
titleNoShort tile title (defaults from human_forward)
user_intentNoquestion | directive | correction | steer | new_task | ack | other
user_utteranceYesUser message that prompted this turn (verbatim or excerpt)
Behavior3/5

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

Discloses what is captured (user utterance, assistant output, auto-aggregated traces). However, no annotations are provided, and the description does not mention auth requirements, side effects, or behavior on repeated calls, leaving gaps.

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 sentences, no wasted words. Front-loaded with core action and key details. Highly efficient.

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?

For a tool with 15 parameters and no output schema, the description provides a high-level overview but lacks detail on return values, prerequisites, or error conditions. Adequate but not comprehensive.

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 coverage is 80%, and the schema already describes parameters well. The description adds no extra parameter detail, so baseline score applies.

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?

Clearly states it mints an RPT v3 agent_response turn tile, specifying the schema version. Differentiates from sibling tools by focusing on recording turn interactions, extending prior convention.

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?

Explicitly says 'Use at end of each assistant turn (lean default)', providing clear context. Does not list alternatives or when not to use, but the instruction is specific enough.

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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