Agent skill

Data Migration

by cbrock84 in cbrock84/headcount

Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values…

MITAuto-check passedDevOps & Cloud

Install Data Migration

skills CLI
$ npx skills add cbrock84/headcount --skill data-migration -a claude-code

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

GitHub CLI
$ gh skill install cbrock84/headcount data-migration --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/cbrock84/headcount.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/technology/skills/data-migration .claude/skills/data-migration && 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/

Facts

Skill name
data-migration
GitHub stars
2k
Token cost
~1.2k tokens
SKILL.md length
669 words
Files
1
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values…

  • DevOps & Cloud work in your project
  • SKILL.md covers Profile the source before you…, Write the mapping down field…, Rehearse on a full copy, more… and Choose the cutover style…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Data Migration is an agent skill from cbrock84/headcount. Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values rather than assuming, handling the records that will not map cleanly, and planning a rollback that is actually executable. Use this to plan or run a migration, assess a migration plan someone else wrote, work out why a completed migration is producing wrong numbers, or size how long one will really take.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud. The repository describes itself as: An agent organization structured as a company — 15+ departments, 125+ skills, each independently installable, citing the standards and regulators that settle the question. Runs… The licence is MIT.

When your agent uses it

  • DevOps & Cloud work in your project

Example prompts

  • “Use the data-migration skill to move data from one system to another without losing it or corrupting it — profiling the source before mapping…”
  • “/data-migration”

What it can do on your machine

Read from SKILL.md and the folder at commit 98d1c17. 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

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data Migration loads about 1.2k tokens when it runs. Until then it costs about 129 tokens; SKILL.md has 669 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~129
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from cbrock84/headcount at commit 98d1c17, republished under its MIT licence (© cbrock84). 669 words, ~1,157 tokens.

Download SKILL.mdSave it as .claude/skills/data-migration/SKILL.md (or your agent's skills folder).
name
data-migration
description
Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values rather than assuming, handling the records that will not map cleanly, and planning a rollback that is actually executable. Use this to plan or run a migration, assess a migration plan someone else wrote, work out why a completed migration is producing wrong numbers, or size how long one will really take.

Data migration

Migrations are estimated as a data-movement problem and turn out to be a data-quality problem. The transfer is the easy part; discovering what the old system actually contains is where the time goes.

Profile the source before you map anything

Look at the real data, not the schema and not what anyone tells you it contains. Every legacy system has fields used for something other than their name, free-text where an enumeration was intended, duplicates that both look canonical, and records predating a rule everyone believes has always applied.

Count distinct values, null rates, format variance, and outliers on every field you intend to move. This is the single highest-return activity in a migration and the one most often skipped in favor of starting the mapping.

Decide what not to move. Migrating everything is the default and rarely the right answer. Archive what has no live use and move a clean subset — it shrinks the mapping, the reconciliation, and the cutover window all at once.

Write the mapping down field by field, including the ugly parts

For each target field: source field, transformation, what happens when the source is empty, and what happens when it does not fit. That last column is the one that decides how the migration goes.

Records that will not map cleanly need a decision, not a default. A row silently dropped, a required field filled with a placeholder, or a truncated value is a defect discovered months later by someone who trusted the number. Route exceptions to a list a human works through, and count them.

Rehearse on a full copy, more than once

A rehearsal on a sample proves the mapping compiles. A rehearsal on a full copy proves the timing, finds the pathological records, and gives you a real number for the cutover window.

Expect several rehearsals. Each one should end with a reconciliation and a defect list, and the last one should be clean and timed. Going into cutover having never completed a full run at production volume means the cutover is the first full run.

Show full SKILL.md (323 more words)Show less

Choose the cutover style deliberately

  • Big-bang — stop, migrate, start on the new system. Simplest to reason about, and the whole risk lands in one window. Viable when the window is affordable and rollback is real.
  • Parallel run — both systems live, one authoritative. Safer and much more expensive, because something has to keep them in step and someone has to reconcile the divergence daily.
  • Phased — by entity, region, or business unit. Reduces blast radius and creates the hardest problem in migration: records that reference each other across the boundary while it exists.

Whichever you pick, name the point of no return and what the rollback is on each side of it. A rollback that has never been executed is not a rollback, and after the new system has taken live writes, reverting means merging them back — which is a second migration nobody planned.

Reconcile on counts and on values

Row counts alone catch a truncated load and nothing else. Reconcile control totals for anything financial, distributions for key fields, and a sample compared record by record. Then have the people who use the data check the records they know by heart — they find things no query will.

Reconcile again a week after cutover. Problems in the ongoing integrations that replaced the migration usually show up then rather than on the day.

Plan for the long tail

Migrations are declared done and then produce findings for months. Keep the source system readable for longer than feels necessary, keep the mapping and the exception lists, and keep someone assigned. The alternative is a question about a historical record that nobody can answer because the old system was decommissioned on schedule.

Never

  • Map from the schema rather than from the data.
  • Let a record fail to map and be dropped without landing on a list someone works.
  • Cut over without a full-volume rehearsal that completed and reconciled.
  • Decommission the source system before the reconciliation window has closed.

© cbrock84, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/technology/skills/data-migration of cbrock84/headcount.

Open the folder on GitHubat commit 98d1c17

Compare with similar skills

Data Migration 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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Data Migration this skillcbrock84/headcount2k—~1.2kAutomated safety check: PassMIT
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Terraform and OpenTofu Guideagentscope-ai/QwenPaw35k6 repos~4.2kAutomated safety check: PassApache-2.0
Vercel Optimize Auditvercel-labs/agent-skills32k8 repos~4.3kAutomated safety check: PassNone
Analyze GitHub Action Logswithastro/astro63k1 repos~1.3kAutomated safety check: PassCustom licence
Docs Learn PR Previewnetdata/netdata81k—~2kAutomated safety check: PassGPL-3.0

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Categories

Questions about Data Migration

What does Data Migration do?

Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values…. Data Migration is an agent skill from cbrock84/headcount. Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values rather than assuming, handling the records that will not map cleanly, and planning a rollback that is actually executable.

When should I use Data Migration?

Data Migration fits situations like: devOps & Cloud work in your project.

How do I install Data Migration in Claude Code?

Run `npx skills add cbrock84/headcount --skill data-migration -a claude-code`. Or copy the skill folder (plugins/technology/skills/data-migration in cbrock84/headcount) into .claude/skills/data-migration in your project. Claude Code loads it when a task matches its description.

How do I install Data Migration in Codex?

Run `npx skills add cbrock84/headcount --skill data-migration -a codex`. Or copy the skill folder (plugins/technology/skills/data-migration in cbrock84/headcount) into .agents/skills/data-migration in your project. Codex loads it when a task matches its description.

Can I use Data Migration 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 cbrock84/headcount --skill data-migration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-migration, .gemini/skills/data-migration, .github/skills/data-migration and .opencode/skills/data-migration in your project.

What does Data Migration need to run?

SKILL.md names no scripts, command-line tools or credentials: Data Migration is instructions for the agent only.

Does Data Migration access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Data Migration 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. Review the folder before installing.

What licence does Data Migration use?

Data Migration 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 Data Migration use?

About 1.2k tokens (SKILL.md is roughly 4.6k 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 Data Migration?

Skills that share tags, products or a category with Data Migration: Monitor CI (nrwl/nx, 29k stars), Terraform and OpenTofu Guide (agentscope-ai/QwenPaw, 35k stars), Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars) and Analyze GitHub Action Logs (withastro/astro, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Data Migration?

cbrock84 (a GitHub user) maintains it in cbrock84/headcount, which has 2,001 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 17, 2026.

Source: cbrock84/headcount on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.