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latent-defense

Latent Defense MCP Server

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preview_ticket_template

Preview ticket templates by dry-rendering them with synthetic content to see rendered title and description before saving, with fallback warnings and provider transform hints.

Instructions

Dry-render a ticket template against synthetic content — no state touched.

Shows what a TicketTemplate will produce before it's saved on a provider. Returns rendered_title / rendered_description, plus fell_back + warning when a template fails to render (the hard-coded body is used instead), and a provider transform_hint (e.g. Jira flattens markdown into ADF). Does NOT modify the saved template on the active provider.

Args: template: JSON object for the TicketTemplate. Common fields: description_template, title_template (Jinja2 source strings); optional per-stage overrides description_template_{initial,final,failure} and title_template_{initial,final,failure}; field_defaults (dict of scalar custom-field defaults). enabled is forced on for the preview render. stage: Lifecycle slice to render — "initial" (creation), "final" (resolution), or "failure". Defaults to "final". provider: Optional provider name; when set, the response includes a transform hint for how that provider will mutate the rendered body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
templateYes
stageNofinal
providerNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description fully discloses behavior: no state modification, exact output fields (rendered_title, rendered_description, fell_back, warning, transform_hint), fallback behavior on failed render, and forced enabled. Despite no annotations, this is comprehensive.

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 front-loaded with the core purpose, then explains output, then details parameters in an Args section. It is slightly verbose but well-organized. No redundant sentences.

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

Completeness5/5

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

The description covers all essential aspects: input parameters, output fields, behavior (no side effects, fallback), and optional provider-specific hints. Given the presence of an output schema, the description provides sufficient context for correct use.

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

Parameters5/5

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

Schema description coverage is 0%, but the description explains each parameter in detail: template (JSON object with common fields), stage (lifecycle slice with defaults), and provider (optional, yields transform hint). This compensates fully for the missing schema descriptions.

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 states the tool dry-renders a ticket template without modifying state. It uses the precise verb 'Dry-render' and specifies the resource 'TicketTemplate', distinguishing it from sibling tools like get_ticket_template_variables or sync_ticket.

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

Usage Guidelines4/5

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

The description implies the tool should be used to preview template output before saving to a provider, but does not explicitly list when not to use it or provide alternatives. The context is clear enough for an agent to infer appropriate usage.

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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