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note_add

Add notes or comments to tickets, tasks, projects, or organizations to document context, decisions, and updates in project management workflows.

Instructions

PROJECT MANAGEMENT (TPM): Add a note/comment to a ticket or task for context or decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_typeYesType of entity
entity_idYesID of the entity
contentYesNote content

Implementation Reference

  • Main tool handler in _handle_tool function. Creates NoteCreate from arguments and calls db.add_note to persist the note, returns confirmation message.
    if name == "note_add":
        note = db.add_note(
            NoteCreate(
                entity_type=args["entity_type"],
                entity_id=args["entity_id"],
                content=args["content"],
            )
        )
        # Return minimal confirmation - note content is echoed back by caller anyway
        return f"Added note {note.id} to {note.entity_type}/{note.entity_id}"
  • Tool registration in list_tools() function, including name, description, and JSON input schema matching NoteCreate model.
        name="note_add",
        description="PROJECT MANAGEMENT (TPM): Add a note/comment to a ticket or task for context or decisions.",
        inputSchema={
            "type": "object",
            "properties": {
                "entity_type": {
                    "type": "string",
                    "enum": ["org", "project", "ticket", "task"],
                    "description": "Type of entity",
                },
                "entity_id": {"type": "string", "description": "ID of the entity"},
                "content": {"type": "string", "description": "Note content"},
            },
            "required": ["entity_type", "entity_id", "content"],
        },
    ),
  • Database implementation of add_note: generates ID, inserts into 'notes' table using SQL, commits, and returns Note model instance.
    def add_note(self, data: NoteCreate) -> Note:
        id = self._gen_id()
        now = self._now()
        self.conn.execute(
            "INSERT INTO notes (id, entity_type, entity_id, content, created_at) VALUES (?, ?, ?, ?, ?)",
            (id, data.entity_type, data.entity_id, data.content, now),
        )
        self.conn.commit()
        return Note(
            id=id,
            entity_type=data.entity_type,
            entity_id=data.entity_id,
            content=data.content,
            created_at=datetime.fromisoformat(now),
        )
  • Pydantic model NoteCreate defining the input structure for note_add tool, used for validation and type hints.
    class NoteCreate(BaseModel):
        entity_type: str
        entity_id: str
        content: str
Behavior2/5

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

With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a safe operation, if it requires specific permissions, how notes are stored, or if there are rate limits. The description adds minimal context beyond the basic action, leaving gaps for a mutation tool.

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 concise and front-loaded with the core action, using a single sentence. However, the parenthetical 'PROJECT MANAGEMENT (TPM)' adds minor noise without clear value, slightly reducing efficiency.

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 no annotations and no output schema, this is a mutation tool with incomplete context. The description lacks details on behavioral traits, error handling, or return values, making it inadequate for safe and effective use by an AI agent.

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%, so the schema fully documents parameters. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or constraints. Baseline 3 is appropriate as the schema handles the heavy lifting.

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 action ('Add a note/comment') and target ('to a ticket or task'), with the purpose ('for context or decisions'). It distinguishes from siblings like note_get or note_list by specifying creation rather than retrieval. However, it doesn't explicitly mention all entity types from the schema (org, project).

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

Usage Guidelines3/5

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

The description implies usage through the phrase 'for context or decisions' and the TPM context, suggesting when to add notes. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like updating tasks/tickets directly, or when not to use it (e.g., for major changes). No sibling tool comparisons are made.

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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