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add_death

Schedule a character's canonical death at a specified chapter with given circumstances and optional death style. Ensures story continuity by formalizing plot events in the guarded chapter pipeline.

Instructions

Schedule a canonical death.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
characterYes
chapterYes
circumstancesYes
death_styleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Core handler logic that appends a DeathEntry to the project's death_schedule and saves.
    def add_death(character: str, chapter: int, circumstances: str, death_style: str = "") -> str:
        proj, _ = require_project()
        proj.death_schedule.append(
            DeathEntry(character=character, chapter=chapter, circumstances=circumstances, death_style=death_style)
        )
        save_project_and_continuity()
        return f"Death scheduled: {character} in chapter {chapter}"
  • DeathEntry data class schema used by add_death.
    @dataclass
    class DeathEntry:
        character: str
        chapter: int
        circumstances: str
        death_style: str = ""
  • MCP tool registration of 'add_death' via @mcp.tool() decorator.
    @mcp.tool()
    async def add_death(character: str, chapter: int, circumstances: str, death_style: str = "") -> str:
        """Schedule a canonical death."""
        return workflow.add_death(character, chapter, circumstances, death_style)
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. 'Schedule' implies non-immediate action, but no details on side effects, permissions, or what happens after scheduling. The output schema exists but is not referenced.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short, consisting of three words. While concise, it omits crucial details and does not earn its place by providing meaning beyond the name.

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?

Given four parameters, an output schema, and no annotations, the description fails to provide enough context for correct invocation. The agent has no guidance on parameter formatting, purpose of death_style, or what the output contains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no information about the four parameters (character, chapter, circumstances, death_style). The agent must rely only on parameter names, which are insufficient.

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 'Schedule a canonical death' clearly states the action (schedule) and what it acts upon (death). It distinguishes from sibling tools like 'mark_character_dead' by implying a scheduled versus immediate event, though it could be more explicit.

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 'mark_character_dead' or 'add_established_fact'. No conditions for use or exclusions are provided, leaving the agent to infer usage context.

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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