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/travisjneuman/.claudeWrote 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/travisjneuman/.claude/deploy)<a href="https://agentmods.dev/commands/travisjneuman/.claude/deploy"><img src="https://agentmods.dev/badge/commands/travisjneuman/.claude/deploy.svg" alt="Measured on agentmods" 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 | $0.00008 | $0.01121 |
| Opus 5 | $0.00004 | $0.00561 |
| Sonnet 5 | $0.00002 | $0.00224 |
| Haiku 4.5 | $0.00001 | $0.00112 |
Grade A, and why
deploy scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sf "$DEPLOY_URL" -o /dev/null && echo "HEALTHY" || echo "UNHEALTHY" How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy Application
Runs a full deployment pipeline: pre-flight checks, build, deploy, health verification, and status report.
Execution Flow
Step 1: Pre-Flight Checks
Before deploying, verify the codebase is ready:
# Ensure clean working tree
git status --porcelain
# Run tests
npm run test 2>/dev/null || pytest 2>/dev/null || go test ./... 2>/dev/null || echo "NO_TEST_RUNNER"
# Run type checks (if applicable)
npm run type-check 2>/dev/null || npx tsc --noEmit 2>/dev/null || mypy src/ 2>/dev/null || echo "NO_TYPE_CHECK"
# Run linter
npm run lint 2>/dev/null || ruff check . 2>/dev/null || golangci-lint run 2>/dev/null || echo "NO_LINTER"
If any check fails: Stop deployment, report the failure, and suggest fixes.
Step 2: Detect Environment
Target: {{target}}
Environment: {{environment}} (default: staging)
If environment is production, add an extra confirmation step:
WARNING: You are deploying to PRODUCTION.
Confirm: Have tests passed? Is this change reviewed?
Step 3: Build
# Build the project
npm run build 2>/dev/null || python -m build 2>/dev/null || go build ./... 2>/dev/null || cargo build --release 2>/dev/null
If build fails: Stop. Report error with context.
Step 4: Deploy by Target
Vercel
# Staging
npx vercel --confirm
# Production
npx vercel --prod --confirm
Pre-requisites: vercel CLI installed, project linked (vercel link).
Docker
# Build image
docker build -t app:latest .
# Tag for registry
docker tag app:latest registry.example.com/app:$(git rev-parse --short HEAD)
# Push
docker push registry.example.com/app:$(git rev-parse --short HEAD)
# Deploy (compose)
docker compose -f docker-compose.{{environment}}.yml up -d
Pre-requisites: Dockerfile exists, Docker daemon running.
AWS
# Detect AWS deployment type
[ -f "serverless.yml" ] && echo "SERVERLESS"
[ -f "cdk.json" ] && echo "CDK"
[ -f "template.yaml" ] && echo "SAM"
[ -f "copilot/.workspace" ] && echo "COPILOT"
# Serverless Framework
npx sls deploy --stage {{environment}}
# AWS CDK
npx cdk deploy --require-approval never
# AWS SAM
sam build && sam deploy --no-confirm-changeset
# AWS Copilot
copilot deploy --env {{environment}}
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.
- 4d ago First seen · 199 lines · 8 tokens per session scan A 55e2eb57c7f1
deploy is a command published in the GitHub repository travisjneuman/.claude (96 stars, last pushed 3d ago), licensed MIT. It adds 8 tokens to every session and 1,121 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
commit-message
Generate a conventional commit message from staged changes.
pr-description
Generate a PR title and description from the current branch diff against main.
work-flow-release
Complete workflow to prepare and publish a release.
work-commit-push-pr
Pointer: Claude Code ships a native /commit-push-pr that owns the commit + push + PR macro. This command adds the foundation's pre-flight gate and convention sources on top — it does not re-implement the macro.
sync
A command that pulls the latest code from the main Git branch and updates the project's key planning and instruction documents to match it.
watch-ci
Spawn a background Haiku-backed subagent to watch CI for the current branch (or specified target). Provider-agnostic — the subagent inspects project signals to identify the CI system (GitHub Actions, GitLab CI, CircleCI, etc.) and picks the right CLI. Returns immediately; reports back when CI reaches a terminal state.