Official agent skill

SQL Server Table Reconciliation

A skill your agent uses when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs…

OfficialMITAuto-check passedBusiness, Finance & HR

Install SQL Server Table Reconciliation

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sql-server-table-reconciliation .claude/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .claude/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/sql-server-table-reconciliation .agents/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .agents/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/sql-server-table-reconciliation .cursor/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .cursor/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/github/awesome-copilot.git --path skills/sql-server-table-reconciliation

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/sql-server-table-reconciliation .gemini/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .gemini/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/sql-server-table-reconciliation .github/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .github/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install github/awesome-copilot sql-server-table-reconciliation --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/sql-server-table-reconciliation .opencode/skills/sql-server-table-reconciliation && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "sql-server-table-reconciliation" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/sql-server-table-reconciliation into .opencode/skills/sql-server-table-reconciliation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sql-server-table-reconciliation", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: sql-server-table-reconciliation
GitHub stars: 40k
Used in: 1 other repo
Token cost: ~1.4k tokens
SKILL.md length: 478 words
Files: 2 (incl. scripts)
Skills in repo: 417
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs…

Works in 6 steps: Collect connection details for source… → Identify primary key / composite key → Detect schema differences → …
: comparing SQL Server tables across instances
SKILL.md covers Workflow, Collect Inputs, Bundled Script and Comparison Rules, plus 4 more sections
Runs Python scripts from its folder; calls python and pip; needs MSSQL_PASSWORD

What it does

SQL Server Table Reconciliation is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Use when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs staging comparison. Uses mssql-python driver with Apache Arrow for fast columnar data transfer and comparison.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/reconcile.py`).

It sits in Business, Finance & HR, covering Accounting and bookkeeping and Data pipelines and ETL. It works with Microsoft SQL Server and Python. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

: comparing SQL Server tables across instances
Data migration validation
ETL verification
Row mismatch detection

Example prompts

“/sql-server-table-reconciliation”

Requirements

Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

Collect connection details for source and target
Identify primary key / composite key
Detect schema differences
Extract data via Arrow for efficient columnar transfer
Compare rows and columns
Generate reconciliation report

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- MSSQL_PASSWORD
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SQL Server Table Reconciliation loads about 1.4k tokens when it runs. Until then it costs about 80 tokens; SKILL.md has 478 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~80
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 478 words, ~1,449 tokens.

Download SKILL.mdSave it as .claude/skills/sql-server-table-reconciliation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: sql-server-table-reconciliation
description: Use when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs staging comparison. Uses mssql-python driver with Apache Arrow for fast columnar data transfer and comparison.

SQL Server Table Reconciliation

Compare identical tables across two SQL Server instances using Python with mssql-python driver and Apache Arrow. Detect missing rows, column mismatches, schema drift, and produce a reconciliation report.

Workflow

Collect connection details for source and target
Identify primary key / composite key
Detect schema differences
Extract data via Arrow for efficient columnar transfer
Compare rows and columns
Generate reconciliation report

Collect Inputs

Parameter	Required	Description
Source server	Yes	Source SQL Server (e.g. `prod-server.database.windows.net`)
Source database	Yes	Source database name
Target server	Yes	Target SQL Server (e.g. `staging-server.database.windows.net`)
Target database	Yes	Target database name
Tables	Yes	Comma-separated `schema.table` names, or `schema.` wildcard (e.g. `dbo.Orders,dbo.Items` or `dbo.`)
Auth mode	Yes	`sql` (user/password) or `entra` (Azure AD/token)
Primary key	Auto-detect	Column(s) forming the row identity. Auto-detect from metadata if not provided.
Columns to compare	All	Subset of columns, or all non-PK columns
Chunk size	`100000`	Rows per batch for large tables
Output format	`console`	`console`, `csv`, `parquet`, or `json`

Bundled Script

The reconciliation logic is provided as a standalone script at scripts/reconcile.py. Invoke it with the appropriate arguments based on user inputs:

bash

python scripts/reconcile.py \
    --source-server <source_server> \
    --source-database <source_database> \
    --target-server <target_server> \
    --target-database <target_database> \
    --tables "<table_spec>" \
    --auth <sql|entra> \
    --chunk-size <chunk_size> \
    --output <console|csv|json>

Optional arguments

Argument	Description
`--primary-key`	Comma-separated PK column(s). Omit to auto-detect.
`--columns`	Comma-separated columns to compare. Omit to compare all non-PK columns.

Example invocations

Single table with SQL auth:

bash

python scripts/reconcile.py \
    --source-server prod-server.database.windows.net \
    --source-database ProdDB \
    --target-server staging-server.database.windows.net \
    --target-database StagingDB \
    --tables "dbo.Orders" \
    --auth sql \
    --output console

Wildcard with Entra auth and CSV output:

bash

python scripts/reconcile.py \
    --source-server prod-server.database.windows.net \
    --source-database ProdDB \
    --target-server staging-server.database.windows.net \
    --target-database StagingDB \
    --tables "dbo.*" \
    --auth entra \
    --output csv

Prerequisites

Install required packages before running:

bash

pip install mssql-python pyarrow pandas

Comparison Rules

Normalize types before comparing: cast decimals to same precision, trim strings, normalize datetime to UTC
NULL handling: NULL == NULL is considered a match (both sides missing = no diff)
Ignore row order: always compare by PK join, never positional
Large tables: chunk extraction with OFFSET/FETCH or ROW_NUMBER() partitioning

Show full SKILL.md (199 more words)Show less

Hash-Based Optimization (for large tables)

When table has >1M rows, generate a hash pre-check:

sql

SELECT {pk_cols},
       HASHBYTES('SHA2_256', CONCAT_WS('|', col1, col2, ...)) AS row_hash
FROM {table}

Compare hashes first; only fetch full rows for mismatched hashes. This reduces data transfer significantly.

Report Format

Reconciling dbo.EMPLOYEES...
Reconciling dbo.DEPARTMENTS...
Reconciling dbo.JOBS...

--- dbo.EMPLOYEES ---
  Source: 107  Target: 107
  Missing: 0  Extra: 0  Mismatches: 0
  Result: ✓ IDENTICAL

--- dbo.DEPARTMENTS ---
  Source: 27  Target: 27
  Missing: 0  Extra: 0  Mismatches: 3
  Result: ✗ DIFFERENCES FOUND

--- dbo.JOBS ---
  Source: 19  Target: 19
  Missing: 0  Extra: 0  Mismatches: 0
  Result: ✓ IDENTICAL

=== Summary: 2 passed, 1 failed, 0 skipped / 3 tables ===

When a single table is provided, include full detail (schema drift, sample rows, mismatches). When multiple tables, use the compact per-table format above with full detail only for tables with FAIL status.

Performance Considerations

Scenario	Strategy
< 100K rows	Single Arrow fetch, in-memory pandas compare
100K–1M rows	Chunked extraction (100K batches), streaming comparison
> 1M rows	Hash pre-check → only fetch mismatched rows
Wide tables (100+ cols)	Compare PK + hash first, drill into specific columns on mismatch
Network-constrained	Use Arrow columnar format (10-50x smaller than row-by-row)

Constraints

Always use mssql-python driver (not pyodbc, pymssql)
Always use Apache Arrow via cursor (cursor.arrow()) for data extraction
Connection MUST use connection string format, not keyword arguments (kwargs like encrypt=True throw errors)
Never compare without identifying PK first — ask user if auto-detect fails
Handle connection failures gracefully with retry logic
Never hardcode credentials in generated scripts — use os.environ / getpass (env vars: MSSQL_USER, MSSQL_PASSWORD)
Do not print credentials in output or logs
Use parameterized queries (? placeholders) for metadata lookups — never f-string interpolate user input into SQL

Files

SKILL.md and 1 other file (scripts) in skills/sql-server-table-reconciliation of github/awesome-copilot.

SKILL.md
scripts/reconcile.py

Open the folder on GitHubat commit 727ff2e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

Kilo-Org/kilo-marketplaceskills/sql-server-table-reconciliation

Compare with similar skills

SQL Server Table Reconciliation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Questions about SQL Server Table Reconciliation

What does SQL Server Table Reconciliation do?

A skill your agent uses when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs…. SQL Server Table Reconciliation is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Use when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs staging comparison.

When should I use SQL Server Table Reconciliation?

SQL Server Table Reconciliation fits situations like: : comparing SQL Server tables across instances; data migration validation; ETL verification; row mismatch detection.

How do I install SQL Server Table Reconciliation in Claude Code?

Run `npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a claude-code`. Or copy the skill folder (skills/sql-server-table-reconciliation in github/awesome-copilot) into .claude/skills/sql-server-table-reconciliation in your project. Claude Code loads it when a task matches its description.

How do I install SQL Server Table Reconciliation in Codex?

Run `npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a codex`. Or copy the skill folder (skills/sql-server-table-reconciliation in github/awesome-copilot) into .agents/skills/sql-server-table-reconciliation in your project. Codex loads it when a task matches its description.

Can I use SQL Server Table Reconciliation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill sql-server-table-reconciliation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sql-server-table-reconciliation, .gemini/skills/sql-server-table-reconciliation, .github/skills/sql-server-table-reconciliation and .opencode/skills/sql-server-table-reconciliation in your project.

What does SQL Server Table Reconciliation need to run?

Going by SKILL.md and its folder, SQL Server Table Reconciliation needs Python for the scripts in its folder, the command-line tools its instructions call (python and pip) and credentials named MSSQL_PASSWORD. Our summary lists: Python 3.

Does SQL Server Table Reconciliation access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is SQL Server Table Reconciliation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does SQL Server Table Reconciliation use?

SQL Server Table Reconciliation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SQL Server Table Reconciliation use?

About 1.4k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SQL Server Table Reconciliation?

Skills that share tags, products or a category with SQL Server Table Reconciliation: Beancount Importer Author (bex-co/beancount-io, 294 stars), Travel Expense Reimbursement (Foxtailsss-Andy/Anna-Agent, 147 stars), Data Throughput Accelerator (affaan-m/ECC, 274k stars) and Bio Copy Number Cnvkit Analysis (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SQL Server Table Reconciliation?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install SQL Server Table Reconciliation

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

SQL Server Table Reconciliation

Workflow

Collect Inputs

Bundled Script

Optional arguments

Example invocations

Prerequisites

Comparison Rules

Hash-Based Optimization (for large tables)

Report Format

Performance Considerations

Constraints

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from github/awesome-copilot

Related

Questions about SQL Server Table Reconciliation