discovery

Falsifiable scene templates — one claim plus what would make it false

get_scene_templates

Read-only

Falsifiable scene templates — one claim plus what would make it false. The cards a story is told with. Each declares truth conditions the data can falsify, so a claim survives on evidence rather than assertion. Persona relevance is derived from focus (a stated heuristic). Drafts excluded unless ?status=all.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_scene_templates"
  }
}

Input Schema

Name	Required	Description
`id`	No	Fetch a single scene template.
`form`	No	Canonical form the scene presents as, e.g. rising.
`tier`	No	1 descriptive \| 2 model-bound \| 3 decision/value.
`focus`	No	Spine focus, e.g. regretted-loss, compensation, cross.
`shape`	No	Data shape, e.g. series, groups, funnel.
`status`	No	published (default) \| all.
`persona`	No	Scenes relevant to one persona.
`archetype`	No	Archetype, e.g. trend, where, flow, driver.

Output Schema

Name	Required	Description	Default
`note`	Yes
`count`	Yes
`filter`	Yes
`scenes`	Yes
`contract`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 8, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already establish read-only and non-destructive behavior, so the bar is lower. The description adds useful behavioral context: drafts are excluded by default unless status=all, and persona relevance is derived from focus via a stated heuristic rather than a direct mapping. It also explains the falsifiability semantics, which an agent could not infer from annotations alone.

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 short and front-loaded with the core concept, but the first sentence repeats the title verbatim and 'The cards a story is told with' is metaphorical rather than informational. The remaining behavioral details are useful and compact, but some words could be trimmed without losing meaning.

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?

For a read-only tool with full schema coverage and an output schema, the description provides enough conceptual and behavioral context for an agent to call it correctly. It explains the default status behavior and the core semantics of scene templates. The missing usage exclusions are already captured under usage guidelines, so this dimension remains fairly complete.

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?

The input schema has 100% description coverage, with meaningful descriptions for all 8 parameters and enums for tier and status. The description adds some extra meaning around status and persona/focus, but does not expand on id, form, shape, or archetype. Since the schema already carries the heavy lifting, the baseline score of 3 is appropriate.

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 identifies a specific resource—falsifiable scene templates—and explains what they are: one claim plus what would make it false. It lacks an explicit verb like 'list' or 'fetch', but the tool name and context make the retrieval purpose obvious. It is distinct enough from sibling tools by focusing on scene templates with truth conditions.

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 is given about when to use this tool versus any of the many sibling get_* tools. The only conditional statement, 'Drafts excluded unless ?status=all', describes a filter behavior rather than a use-case selector or alternative tool. An agent is left to infer when scene templates are the right resource.

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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