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memory_create_issue

Record issues and bugs as persistent memories with status, severity, and component fields. Tagged automatically for easy retrieval.

Instructions

Create a new issue/bug memory.

Args: content: Description of the issue status: Issue status - "open" (default) or "closed" closed_reason: If closed, the reason - "complete" or "not_planned" severity: Issue severity - "critical", "major", "minor" (default) component: Component/area affected (e.g., "graph", "storage", "api") category: Issue category (e.g., "bug", "enhancement", "performance")

Returns: Created issue memory with auto-assigned tag "memora/issues"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
statusNoopen
closed_reasonNo
severityNominor
componentNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided. The description discloses the return value and auto-assigned tag, but does not discuss side effects, permissions, or whether it's safe (obviously creates, but no explicit safety info). Partial transparency.

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?

The description is structured with Args and Returns sections. It is informative without being verbose, though it could be slightly more concise. Overall well-organized.

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 existence of an output schema (not shown but referenced), the description covers all 6 parameters with 1 required and explains the return. It lacks error cases but is sufficient for a creation tool.

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 description coverage is 0%, so the description must add meaning. It provides clear explanations for each parameter (e.g., status defaults to 'open', severity options) and clarifies the return value, adding significant value 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 specifies the action ('Create a new issue/bug memory') and resource (issue/bug memory). The name and description distinguish it from siblings like memory_create (generic) and memory_create_todo (todo-specific).

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like memory_create or memory_create_todo. The description does not mention when not to use it or any prerequisites.

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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