What is typesncolumns?

A prompt for documenting the properties returned by a PowerShell command. It asks the writer to trace different execution paths and update the command's built-in help with output columns and types.

Use it when documenting PowerShell command output, such as property names, data types, descriptions, and the conditions under which each result appears.

It reduces incomplete output documentation, including cases where switches or input types change the returned object.

How dataplat/dbatools configures GitHub Copilot

About the project

dbatools is a PowerShell toolkit for automating SQL Server administration and moving SQL Server instances between environments. It is for database administrators who manage SQL Server systems and migrations.

dataplat/dbatools · 2,858 stars · on GitHub · dbatools.io

Reuse

Borrowing it

Nothing to install: this file belongs to dataplat/dbatools. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/dataplat/dbatools/development/.github/prompts/typesncolumns.md

Clone the repo

git clone --depth 1 https://github.com/dataplat/dbatools

Made for: GitHub Copilot.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/dataplat/dbatools/typesncolumns/github.svg)](https://agentmods.dev/commands/dataplat/dbatools/typesncolumns)

Your own site

<a href="https://agentmods.dev/commands/dataplat/dbatools/typesncolumns"><img src="https://agentmods.dev/badge/commands/dataplat/dbatools/typesncolumns/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/dataplat/dbatools/typesncolumns"><img src="https://agentmods.dev/badge/commands/dataplat/dbatools/typesncolumns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,585 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.01585
Opus 5.5	$0.00000	$0.00634
Sonnet 5.5	$0.00000	$0.00317
Haiku 4.5	$0.00000	$0.00159

Measured 1mo ago against content hash 43e9a1d60135, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

typesncolumns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/prompts/typesncolumns.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prompt for AI to analyze PowerShell command output columns

You are analyzing a PowerShell command file to document its output properties/columns.

Task

Review the provided PowerShell command code, identify all output properties/columns that are returned to the user, and update the .OUTPUTS section in the file's comment-based help.

Instructions

Trace all execution paths including:
- Default output
- Switch parameters that modify output (like -Detailed, -Simple, -Raw, etc.)
- Conditional logic that changes what's returned
- Different outputs for different input types
For each execution path, identify:
- The complete list of property names
- The data type of each property (string, int, bool, datetime, custom object, etc.)
- A brief description of what each property contains
- Which path(s) return this property set
Focus on user-visible output:
- Properties added via Select-Object, Add-Member, or PSCustomObject creation
- Properties from objects being passed through or returned
- Ignore internal/private variables not included in output
Handle common dbatools patterns:
- Select-DefaultView - note which properties are shown by default vs available
- Pipeline objects with added properties
- Different object types returned based on conditions
Research SMO and .NET objects:
- When the output is a Microsoft.SqlServer.Management.Smo.* object, search learn.microsoft.com for the object documentation
- Verify which properties actually exist on the SMO object before listing them
- Only list properties that are documented or that you can confirm exist
- Use the Microsoft documentation as the authoritative source for SMO object properties
- If you cannot find documentation or verify a property exists, do not include it in the "Additional properties" section
Update the file:
- Locate the existing .OUTPUTS section in the comment-based help (within the <# ... #> block)
- Replace the entire .OUTPUTS section with your new documentation
- If no .OUTPUTS section exists, add it after .PARAMETER sections and before .EXAMPLE
- Preserve all other parts of the comment-based help exactly as they are
- Maintain the original indentation style of the file

Read the full file on GitHub · 157 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 157 lines · 0 tokens per session scan A 43e9a1d60135

Subscribe to this mod's changes

typesncolumns is a command published in the GitHub repository dataplat/dbatools (2,858 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,585 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.

Languages Writing and docs best-practices database-administration migrations powershell sql-server sql-server-migration

typesncolumns next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
typesncolumnsdataplat/dbatools	Command	2.9k	4d ago	MIT	A	0	GitHub Copilot
rust-developerhmohamed01/claude-code-plugins	Command	7	1mo ago	none	A	22	Claude Code
generate-typesHKTITAN/cursor-best-practices	Command	7	8mo ago	MIT	A	0	Claude Code
auditofershap/go-best-practices	Command	2	8mo ago	MIT	A	12	Claude Code
auditofershap/python-best-practices	Command	1	8mo ago	MIT	A	12	Claude Code
triagejuan294/cc-rpi	Command	5	3d ago	MIT	A	0	Claude Code
azure-graph-dotnet:deploy-azureTheLobbi/Claude-m	Command	18	1mo ago	none	A	57	Claude Code

dbatools: Command for GitHub Copilot