Borrowing it
Nothing to install: this file belongs to xetenet/xete-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xetenet/xete-mcp/main/.claude/skills/git-discipline/SKILL.mdgit clone --depth 1 https://github.com/xetenet/xete-mcpWrote 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.
[](https://agentmods.dev/skills/xetenet/xete-mcp/git-discipline)<a href="https://agentmods.dev/skills/xetenet/xete-mcp/git-discipline"><img src="https://agentmods.dev/badge/skills/xetenet/xete-mcp/git-discipline/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.
<a href="https://agentmods.dev/skills/xetenet/xete-mcp/git-discipline"><img src="https://agentmods.dev/badge/skills/xetenet/xete-mcp/git-discipline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00066 | $0.00499 |
| Opus 5 | $0.00033 | $0.00249 |
| Sonnet 5 | $0.00013 | $0.00100 |
| Haiku 4.5 | $0.00007 | $0.00050 |
Grade A, and why
git-discipline 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 10d 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.
What it actually says
Git Discipline
When agents write code unattended, commits are the save points. Big commits mean big rollbacks.
Commit rules
- Atomic: one logical change per commit, target ~100 changed lines, hard ceiling ~300. If a diff exceeds the ceiling, split it before committing — not after review finds a problem.
- Always green: the repo compiles and tests pass at every commit.
cargo check/cargo test(or the project's test command) runs before every commit, not just before push. A commit that breaks the build destroys its value as a save point. - Message format:
<area>: <imperative summary>plus, when applicable,SPEC-<feature>: task NandDDR: reviews/DDR-<name>.md. The message states WHY when the diff alone doesn't. - No mixed concerns: formatting-only changes, dependency bumps, and logic changes are separate commits. A reviewer must be able to read a logic diff without whitespace noise.
Branch rules
- Feature branches per SPEC:
feat/<spec-name>. Contract work never lands directly on main. - Agent sessions (Remote Control, owl-alpha bulk work) commit to their feature branch freely; merging to main requires the DDR verdict SHIP for contract paths.
- Rebase before merge; main stays linear. Force-push only on your own feature branches.
Session start ritual (Remote Control especially)
git status— confirm clean tree before new work; stash or commit anything dangling with an explicit message.git log --oneline -5— confirm you're building on what you think you are.- Confirm current branch matches the SPEC being executed.
Recovery posture
- Prefer
git revertover history rewriting on shared branches. - Before any risky operation (rebase, reset, filter), note the current HEAD SHA in the session so it can be restored.
- If an agent session produced a tangle: branch from the last good commit and cherry-pick, rather than untangling in place.
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.
- 10d ago First seen · 34 lines · 66 tokens per session scan A 664f3ab27f0f
git-discipline is a skill published in the GitHub repository xetenet/xete-mcp (0 stars, last pushed 23d ago), licensed MIT. It adds 66 tokens to every session and 499 once invoked, about $0.0003 per session on Opus 5. 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 2026-08-31.
Other skills, from other repositories
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.
repo-ship
Split existing repository work into commits by intent as it happens, or give a new repository its name, visibility, description, and topics at creation. Use the matching path when work is about to be committed or pushed, before a push that would otherwise land as one large commit, or when a new repository is being…
repository-manager-bulk-git-operations
Bulk, parallel git operations across a whole workspace of repositories via the repository-manager MCP server — clone, pull, push, add, commit, pre-commit, phased push, and enumerate every repo across a GitLab instance / GitHub org into an ingest manifest (which also natively ingests them into the knowledge graph as…
source-command-improve
Run ONE iteration of the continuous-improvement loop — pick the highest-value backlog item, implement it, verify end-to-end, commit.
git-workflow
Git workflow patterns including branching strategies, commit conventions, merge vs rebase, atomic commits, worktrees, change summaries, and disciplined version control for AI agents and developer teams.
legacy-shield
Secure zero-knowledge document vault for AI agents. Persistence for your secrets.