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templetwo
by templetwo

reflection_ack

Acknowledge machine-generated reflections to improve signal-to-noise tracking. Use confirm, engage, or discard actions to close the ack-loop.

Instructions

Acknowledge a machine-generated reflection. Closes the ack-loop for the synthesis daemon's signal-to-noise tracking. action: 'confirm' = accurate observation worth promoting; 'engage' = real question, opening a thread; 'discard' = nonsense / cliché / off-topic. To promote a reflection to a chronicle insight, do an explicit record_insight call citing the reflection — this tool does NOT auto-promote (layer hygiene).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reflection_idYesThe id field from recall_reflections output.
actionYesAck action.
noteNoOptional rationale for the ack.
byNoOptional instance id for audit (e.g. 'opus-4-7-mac-studio').
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the three actions and states the tool does not auto-promote, but does not disclose side effects, permanence, or what happens to the reflection after acknowledgment. The description is adequate but lacks depth on behavioral traits.

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?

The description is concise (5 sentences) and front-loaded with the main purpose. It efficiently conveys the action options and the critical caveat about not auto-promoting, with no unnecessary words.

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?

Given no output schema, the description should inform the agent about the return value or result, but it does not. It also does not mention prerequisites (e.g., reflection existence) or state changes. The description is sufficient for basic use but lacks completeness for a full understanding.

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?

The input schema has 100% description coverage, so the description adds marginal value. It rephrases the action options and mentions the 'note' parameter as optional rationale, but does not significantly enhance understanding beyond the schema.

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 the tool's purpose: 'Acknowledge a machine-generated reflection.' It specifies the resource (reflection), the verb (acknowledge), and distinguishes from sibling tools like 'record_insight' by explicitly noting this tool does not auto-promote.

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?

The description explicitly explains when to use each action (confirm, engage, discard) and provides a clear alternative: 'To promote a reflection to a chronicle insight, do an explicit record_insight call citing the reflection — this tool does NOT auto-promote.'

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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