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maintain_memory_lifecycle

Perform explicit lifecycle maintenance on error memory and recover safe prepared card writes, keeping verified fixes accessible for AI coding agents.

Instructions

Run explicit lifecycle maintenance and recover safe prepared card writes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It only states that it 'runs explicit lifecycle maintenance' and 'recovers safe prepared card writes', but does not explain side effects, required permissions, whether actions are destructive, or what 'safe' means. This is critically opaque for an operation-oriented tool.

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 sentence with no wasted words, which is concise in length. However, the phrasing is unclear and not front-loaded with a plain-language explanation of the tool's primary purpose, making it less effective than it could be despite its brevity.

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

Completeness1/5

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

Despite having an output schema, the description is wholly inadequate for a specialized tool. It does not explain the underlying concept of 'cards', what lifecycle maintenance entails, when recovery is needed, or what the output represents. With no annotations and no parameter guidance, this leaves the agent without essential context to use the tool correctly.

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?

The tool has 0 parameters, so the baseline for this dimension is 4. The description does not need to elaborate on parameter meanings because there are none, and the empty input schema is fully consistent with this.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses vague, domain-specific jargon ('lifecycle maintenance', 'safe prepared card writes') without explaining what these mean or what the tool actually does. It is not a tautology, but it fails to clearly identify the tool's action and resource, especially compared to siblings like assemble_context and manage_memory.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as assemble_context or manage_memory. There are no conditions, prerequisites, or exclusions mentioned, leaving the agent without any signal for tool selection.

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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