Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/zevtos/agentpipeWrote 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/commands/zevtos/agentpipe/deploy)<a href="https://agentmods.dev/commands/zevtos/agentpipe/deploy"><img src="https://agentmods.dev/badge/commands/zevtos/agentpipe/deploy/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/commands/zevtos/agentpipe/deploy"><img src="https://agentmods.dev/badge/commands/zevtos/agentpipe/deploy.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 | $0.00022 | $0.00875 |
| Opus 5.5 | $0.00009 | $0.00350 |
| Sonnet 5.5 | $0.00004 | $0.00175 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
deploy 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are orchestrating deployment preparation. This is the final gate before code reaches production. Be thorough — catching issues here is 100x cheaper than catching them in production.
Context
@CLAUDE.md
Auto-context
- Branch: !
git branch --show-current - Status: !
git status --short - Recent commits: !
git log --oneline -10 - Uncommitted changes: !
git diff --stat
Pipeline
Step 1: Pre-flight Checks
Run these checks sequentially, stopping on any failure:
- Clean working tree: No uncommitted changes (warn if found)
- Tests pass: Run the full test suite
- Build succeeds: Run the project build command
- No debug artifacts: Search for
console.log,debugger,binding.pry,import pdb,TODO,FIXME,HACKin changed files since last release tag — warn if found - Environment config: Compare
.env.exampleagainst actual env var usage in code — flag any undocumented variables
Step 2: Security Scan (DevOps Agent)
Run the devops agent:
"Run a deployment security scan:
- Dependency vulnerability scan (npm audit / pip-audit / cargo audit / trivy fs)
- Check for hardcoded secrets (search for API keys, tokens, passwords in source)
- Check Docker image if Dockerfile exists (base image pinned? multi-stage? non-root?)
- Verify security headers are configured (CSP, HSTS, X-Frame-Options)
- Check that production error handling doesn't leak stack traces Report: [PASS / FAIL with findings]"
Step 3: Reviewer Quick Check (Reviewer Agent)
Run the reviewer agent on changes since last release:
"Quick review of all changes since the last release tag.
Focus on: breaking API changes, data model changes that need migration, configuration changes that need deployment coordination.
This is NOT a full code review — just catch deployment-blocking issues."
Step 4: Changelog (Docs Agent)
Run the docs agent:
"Generate a changelog for deployment.
Commits since last tag: !git log $(git describe --tags --abbrev=0 2>/dev/null || echo HEAD~20)..HEAD --oneline
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 · 95 lines · 22 tokens per session scan A 740c27ea9f45
deploy is a command published in the GitHub repository zevtos/agentpipe (11 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 875 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
land
Resolve and squash merge one named, currently authorized pull request.
quality
A command for temporarily clearing a release quality gate or one named check, while recording the reason and expiry time. A quality gate is a required check that normally blocks completion or release.
release-notes
Generate consistent, well-structured release notes from git history. Triggered on release tags following semver patterns (v..) to produce categorized changelog with breaking changes, features, fixes, and contributor attribution.
create-pr
Push the current branch and open a pull request into main with a structured description derived from the branch's commits and the open issues it resolves.
release-manager
Automated release coordination and deployment with ruv-swarm orchestration for seamless version management, testing, and deployment across multiple packages.
doc-changelog
Generation and maintenance of the project changelog.