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gnosys_reflect

Record an outcome as a reflection memory to update confidence, link related memories, and reinforce or contradict prior knowledge.

Instructions

Record an outcome as a new reflection memory, returning its ID, confidence delta, updated memory IDs and confidences, and relationship count. memoryIds defaults to up to five keyword matches on outcome; success defaults to true and confidenceDelta to +0.05 on success or -0.1 on failure, clamping resulting confidence to 0.05..1. Success also reinforces targets and adds validates links; failure adds contradicts links. Use gnosys_reinforce instead for usefulness feedback without creating an outcome memory; each reflection call creates a new record and applies the delta again.

Input Schema

NameRequiredDescriptionDefault
notesNoAdditional notes
outcomeYesWhat happened (the outcome to reflect on)
successNoWas it a success? (default: true)
memoryIdsNoMemory IDs to relate to (default: FTS match on outcome)
projectRootNoProject root path; routes the call to that project's store.
confidenceDeltaNoConfidence change (default +0.05 on success, -0.1 on failure); resulting confidence clamps to 0.05..1

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / confidenceDelta / description
      Previous value: -"Custom confidence delta (e.g. 0.1 or -0.2)"New value: +"Confidence change (default +0.05 on success, -0.1 on failure); resulting confidence clamps to 0.05..1"
  2. First observedv7.0.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare non-readonly, non-idempotent, non-destructive, closed-world, but the description adds substantial behavior: default deltas, clamping to 0.05..1, that success reinforces targets and adds validates links while failure adds contradicts links, and the return payload. This is exactly the kind of write-operation semantics the annotations cannot convey.

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

Conciseness4/5

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

Front-loads the return payload then the parameter defaults then the sibling alternative, with no wasted sentences. It is dense and packs several clauses into the middle sentence, but every clause carries information.

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?

No output schema exists, yet the description enumerates the returned fields (ID, confidence delta, updated memory IDs and confidences, relationship count) and explains side effects on linked memories. Nothing needed to invoke it correctly or interpret its result is missing.

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%, so baseline is 3, but the description adds meaning beyond the schema: memoryIds defaults to 'up to five keyword matches on outcome', and success/confidenceDelta defaults are tied to each other and the clamping rule. Minor overlap with schema text keeps it from a 5.

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?

States a specific verb and resource: 'Record an outcome as a new reflection memory', and lists what it returns. It explicitly names the sibling gnosys_reinforce as the alternative, so an agent can distinguish the two without opening either schema.

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?

Explicitly routes the agent: 'Use gnosys_reinforce instead for usefulness feedback without creating an outcome memory', and warns that each reflection call creates a new record and reapplies the delta. Both the when-to-use and the when-to-use-something-else conditions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.