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generate_project_doc

Create full Markdown documentation for ServiceNow apps by extracting live data on data model, business logic, UI, integrations, and security.

Instructions

Generate comprehensive technical documentation for a ServiceNow application by pulling live data from the instance.

Produces a full Markdown document with:

  • Executive overview and architecture diagram

  • Data model (fields, mandatory markers, reference links)

  • Business logic (BRs, Script Includes with method listing)

  • UI layer (Client Scripts, UI Actions by table)

  • Integration points (Scripted REST APIs)

  • Automation (Scheduled Jobs, Notifications)

  • Security (ACLs per table, scope isolation)

  • Operations guide (monitoring, maintenance, common issue matrix)

  • Change log template

The document is ready to paste into Confluence, GitHub Wiki, or any Markdown renderer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_nameYesApplication name for the document title
tablesYesTables that belong to this application (e.g. ["incident","problem"])
scopeNoApplication scope prefix (e.g. "x_mycompany_myapp")
authorNo
versionNo1.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions pulling live data but does not disclose side effects, permissions, rate limits, or that the tool is read-only. The output format is described, but key behavioral aspects are missing.

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 well-structured with a clear first sentence followed by a bullet list of contents. It is informative without being overly verbose, though some minor redundancy exists.

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

Completeness3/5

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

Given the tool's complexity (generating full documentation) and the absence of annotations and output schema, the description adequately covers the output structure but lacks details on parameter usage, behavioral context, and potential limitations.

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 60% (3 of 5 parameters have descriptions). The description adds no extra meaning beyond the schema; it does not explain how parameters affect the generated document or provide examples beyond the schema's brief descriptions.

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 generates comprehensive technical documentation for a ServiceNow application, with a detailed list of contents. It distinguishes itself from sibling tools like 'generate_docs' or 'generate_migration_guide' by its specific focus on live data and full project documentation, though it does not explicitly contrast them.

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 explicit guidance on when to use this tool versus alternatives. The description implies use for generating full documentation but does not mention prerequisites, exclusions, or when not to use it.

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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