Install
$ agentstack add skill-firstp1ck-pi-coding-agent-forge-dolt-database-version-control ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Dolt Database Version Control
Use this skill to decide how, when, why, and where to use Dolt, and to produce safe adoption plans for Dolt-backed systems.
When to use
Use this skill when the user asks about any of the following:
- Dolt, DoltHub, Hosted Dolt, DoltLab, DoltgreSQL/Doltgres, or "Git for data".
- Version-controlling relational data with branches, commits, diffs, merges, remotes, or pull-request-like workflows.
- Adding audit history, rollback, review-before-publish, or branch-per-user changes to an application database.
- Creating a versioned MySQL or MariaDB replica for queryable history, disaster recovery, debugging, or change-data-capture-like workflows.
- Comparing Dolt against Git+CSV, temporal tables, soft deletes, slowly changing dimensions, CDC pipelines, event sourcing, plain MySQL, or Postgres.
- Designing commands, SQL procedures, or rollout checks for a Dolt proof of concept.
Do not use this skill for generic Git, generic SQL, or generic MySQL/Postgres administration unless Dolt or database version control is materially involved.
Inputs and assumptions
Before recommending Dolt, identify:
- The current database engine, SQL dialect, schema size, write/read throughput, data sensitivity, and deployment topology.
- Whether the goal is application-primary storage, collaborative dataset management, audit/disaster recovery, local agent memory, or a versioned replica beside an existing database.
- Whether MySQL-compatible clients are acceptable. If Postgres compatibility is mandatory, treat Doltgres/DoltgreSQL as a separate maturity decision and verify current status from official sources.
- Whether immutable history conflicts with retention, privacy, right-to-erasure, or secret-handling requirements.
- Whether users need branch/merge conflict resolution and who will review or resolve conflicts.
Use references/dolt-guide.md as the packaged baseline. For current versions, installation commands, hosted offerings, maturity labels, or production claims, verify against official Dolt docs or the DoltHub GitHub repositories before finalizing.
Portable workflow
- Classify the Dolt job
primary-app-db: Dolt is the serving SQL database and the app uses branches, diffs, logs, rollback, or review workflows.collaborative-data-repo: Dolt is used from the CLI for CSV/table data collaboration, remotes, pull/push, and reproducible datasets.versioned-replica: Dolt follows an existing MySQL/MariaDB primary to provide an immutable, queryable audit log and recovery aid.evaluation-only: the user needs a recommendation, comparison, architecture review, or proof-of-concept plan.
- State why Dolt is or is not a fit
- Strong fit: relational data needs Git-like branch/merge/diff/log/rollback semantics; application users need review-before-publish; teams need local clones/remotes for data; auditors need row/cell history; operators want a versioned replica of MySQL.
- Weak fit: the system only needs ordinary backups, simple CRUD, or append-only analytics; the team cannot tolerate MySQL-compatibility gaps; write throughput requires multi-primary horizontal scaling; conflict resolution has no clear owner; immutable history is a liability.
- Choose where Dolt belongs
- In the serving path as a MySQL-compatible database server when app features require branchable versioned data.
- Next to an existing MySQL/MariaDB primary as a read-only/versioned replica when migration risk is high but audit/history is valuable.
- On developer machines or CI for import/diff/merge validation of tabular datasets.
- In DoltHub/Hosted Dolt/DoltLab workflows when the team needs hosted collaboration, cloud operation, or self-hosted sharing.
- Plan how to use it
- Start with a throwaway repository or isolated server; never begin on production data.
- Configure commit identity with
dolt config --global --add user.name ...anddolt config --global --add user.email .... - For CLI workflows, use Git-like commands:
dolt init,dolt table import,dolt status,dolt add,dolt commit,dolt diff,dolt branch,dolt checkout,dolt merge,dolt log,dolt push, anddolt pull. - For SQL workflows, use a MySQL-compatible client with
dolt sql-server; read version-control state through system tables/table functions such asdolt_log,dolt_status,dolt_diff(...), anddolt_history_; write version-control state through procedures such asDOLT_ADD,DOLT_COMMIT,DOLT_CHECKOUT, andDOLT_MERGE. - Prefer primary keys for tables so diffs and merges are meaningful.
- For versioned replicas, validate row-based binlog replication, GTID auto-positioning, unique
server_id, replica warming, and restart/filter behavior before relying on it.
- Produce an adoption recommendation
- Include: recommended Dolt role, fit rationale, commands or SQL sketch, migration/rollback path, operational risks, validation checklist, and a confidence level.
- Separate verified facts from assumptions and explicitly name anything that still needs benchmark, compatibility, or production testing.
Decision checklist
Answer these before saying "use Dolt":
- What exact version-control feature is needed: branch, merge, diff, log, blame/history, rollback, remote sync, or pull-request-style review?
- Is MySQL compatibility acceptable for the application and tooling?
- Can the workload fit a single primary write bottleneck with read replicas, or is a different database architecture required?
- How will branch conflicts be detected, reviewed, and resolved?
- Which data may not be stored in immutable history?
- What proof will show Dolt works here: client compatibility tests, SQL syntax coverage, import size, write throughput, merge behavior, replication drift checks, backup/restore, or disaster-recovery drill?
Safety and side effects
- Ask for confirmation before commands that mutate, delete, rewrite, publish, or connect production systems:
dolt reset --hard,dolt clean,dolt gc,dolt filter-branch, destructive SQL, replication reconfiguration, remotepush, or production imports. - Do not run install commands requiring root/admin privileges unless the user explicitly approves.
- Do not claim Dolt is a drop-in replacement for a specific MySQL workload until the user's schema, queries, migrations, clients, and operational requirements have been tested.
- Treat Dolt history as durable. Do not import secrets, regulated data, or personal data without an explicit retention/privacy plan.
- For replication, do not change binlog/GTID settings on a production primary without a reviewed database operations plan.
- Prefer read-only diagnostics and disposable proof-of-concept repositories before touching live databases.
Scripts, references, and dependencies
- Reference guide:
references/dolt-guide.md. - Contract tests:
tests/test_contract.py. - No runtime dependencies are bundled.
- Optional external tools, depending on the user's task:
dolt, a MySQL-compatible client, Docker, or access to official Dolt documentation.
Verification
For skill/package maintenance, from the package root run:
npm test
npm pack --dry-run
For a Dolt recommendation or proof of concept, verify with the smallest relevant checks:
dolt version
dolt status
dolt log
dolt diff
SQL server checks, when applicable:
SELECT active_branch();
SELECT * FROM dolt_log LIMIT 5;
SELECT * FROM dolt_status;
CALL DOLT_COMMIT('-am', 'test commit');
Application checks should include client/ORM connection, migration replay, representative queries, branch/merge scenarios, backup/restore, and workload benchmarks before production use.
Pi adapter
- In Pi, use web/documentation search for current Dolt facts before making version-specific, release-specific, or hosted-service claims.
- For unfamiliar repositories, inspect the project structure before recommending Dolt integration points.
- If the user wants this skill enabled after installation, ask before changing Pi settings or symlinks.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Firstp1ck
- Source: Firstp1ck/pi-coding-agent-forge
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.