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add_user_directive_note

Add a structured note to the AI's directive database for persistent record-keeping of implementation details, errors, and user feedback.

Instructions

Add note to user_directives.db notes table for AI record-keeping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesNote content/message
note_typeYes'implementation', 'validation', 'execution', 'dependency', 'error', 'optimization', 'user_feedback', 'lifecycle', 'testing', 'general'
reference_typeNoType of reference: 'directive', 'helper', 'dependency', 'file'
reference_nameNoName of referenced entity (e.g., directive name, helper name, file path)
reference_idNoOptional ID linking to user_directives, helper_functions, etc.
severityNo'info', 'warning', 'error' (default 'info')info
metadata_jsonNoAdditional context as JSON string
Behavior2/5

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

Annotations provide minimal info (not read-only, not destructive). The description adds no behavioral details beyond the action. It does not disclose side effects, authorization needs, rate limits, or error behavior. For a mutation tool with sparse annotations, more transparency is needed.

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 a single sentence with no wasted words. It is concise and directly states the purpose. However, it lacks structure (e.g., sections, bullet points) and is not front-loaded with key info beyond the initial verb. Still, every word earns its place.

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

Completeness2/5

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

Given the tool has 7 parameters, 2 required, no output schema, and sparse annotations, the description is insufficient. It does not explain return values, error behavior, or provide complete context for an agent to use it effectively without additional knowledge.

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 description coverage is 100% (all 7 parameters have schema descriptions). The description does not add any additional meaning beyond what the schema provides. Baseline score of 3 is appropriate as the schema already defines parameters adequately.

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

Purpose4/5

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

The description clearly states the tool adds a note to the user_directives.db notes table for AI record-keeping. The verb 'Add' and resource 'note' are specific. However, it does not differentiate itself from sibling tools like 'add_note' or 'add_tracking_note', which are generic.

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 vs alternatives. It only mentions 'for AI record-keeping', which is vague. No exclusions, prerequisites, or when-not-to-use information is provided.

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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