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clawmem-ai

clawmem-mcp-server

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by clawmem-ai

memory_review

Prompts you with a structured self-review checklist to capture and retain memory and skill insights, preventing knowledge drift. Use after complex tasks or when nudged.

Instructions

Return the ClawMem self-review checklist so durable memory and kind:skill playbooks accumulate instead of drifting. Returns memory-track and skill-track questions. Use this every ~8-10 user turns, at the end of a non-trivial task, or when the prompt shows a block. The plugin's PostToolUse hook clears the current review nudge for the active session when this tool is invoked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoWhich review track to return. Defaults to both.
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 discloses that invoking the tool clears the review nudge, a side effect. However, it does not explicitly state that the operation is read-only and non-destructive, which would be helpful given the lack of annotations.

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 two sentences, front-loaded with the core purpose, followed by usage and side-effect details. Every sentence adds value with no redundancy or filler.

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

Completeness4/5

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

Given the simplicity (one parameter, no output schema, no annotations), the description covers purpose, usage, and a behavioral detail. It could be more complete by describing the expected output format, but it is sufficient for an agent to understand the tool.

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 100% for the single parameter 'focus', with an enum and description. The description adds only that it defaults to 'both', which is also implied by the schema. Thus, the description does not add significant meaning beyond the schema, meeting the baseline for high coverage.

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 returns a ClawMem self-review checklist with memory-track and skill-track questions. It uses a specific verb ('return') and resource ('checklist'), and distinguishes from sibling tools like memory_list and memory_recall which handle storage rather than review.

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?

The description provides explicit guidance on when to use the tool: every ~8-10 user turns, after non-trivial tasks, or when a <clawmem-review-nudge> appears. It also mentions that the nudge is cleared upon invocation. However, it does not explicitly state when not to use it or mention alternatives.

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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