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.
npx skills add softspark/ai-toolkit --skill deploygit clone --depth 1 https://github.com/softspark/ai-toolkitWrote 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/softspark/ai-toolkit/deploy)<a href="https://agentmods.dev/skills/softspark/ai-toolkit/deploy"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/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/skills/softspark/ai-toolkit/deploy"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/deploy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 60 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00027 | $0.00732 |
| Opus 5 | $0.00014 | $0.00366 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00003 | $0.00073 |
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 5d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy Application
$ARGUMENTS
Deploy application to target environment.
Project context
- Docker config: !
cat docker-compose.yml 2>/dev/null || cat Dockerfile 2>/dev/null || echo "no-docker"
Usage
/deploy [environment]
What This Command Does
- Validates deployment prerequisites
- Runs pre-deployment checks
- Executes deployment
- Verifies deployment success
Environments
| Environment | Description |
|---|---|
dev |
Development environment |
staging |
Staging/QA environment |
prod |
Production environment |
Pre-Deployment Checklist
Run automated pre-deployment checks:
python3 ${CLAUDE_SKILL_DIR}/scripts/pre_deploy_check.py [environment]
Returns JSON with pass/fail for each check:
git_clean- no uncommitted changesbranch- on main/master for productiondocker- services running (if applicable)env_file- .env or .env.$ENV existsbuild_artifacts- dist/build presenttests_ran- test result artifacts found
Manual verification:
- Tests passing
- Build successful
- Environment variables set
- Secrets configured
- Database migrations ready
- Rollback plan documented
Deployment Strategies
| Strategy | Use Case |
|---|---|
| Rolling | Zero-downtime, gradual |
| Blue-Green | Instant switch, easy rollback |
| Canary | Risk mitigation, gradual traffic |
| Recreate | Simple, allows downtime |
Output Format
## Deployment Report
### Status: Success / Failed
### Details
- **Environment**: [env]
- **Version**: [version]
- **Started**: [timestamp]
- **Completed**: [timestamp]
### Steps
1. [Step 1] - Done
2. [Step 2] - Done
3. [Step 3] - Failed (if failed)
### Health Check
- [endpoint]: [status]
### Rollback
If needed: `[rollback command]`
PRODUCTION SAFETY
- Always deploy to staging first
- Verify health checks pass
- Have rollback plan ready
- Monitor after deployment
MANDATORY: Documentation Update
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 131 lines · 27 tokens per session scan A 2f87560793eb
deploy is a skill published in the GitHub repository softspark/ai-toolkit (170 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 732 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
surface-after-care
Regelmäßiger Pflegedurchlauf für ein bereits veröffentlichtes GitHub-Repository (Stufe 1, günstig und oft wiederholbar): zuerst alle Distributionsflächen des Projekts ermitteln (npm, PyPI, Registries, Marketplaces, Stores, Website) und Änderungen später dorthin spiegeln, dann Topics setzen, Privacy-Gate, Dokumente auf…
github-repo-care
Protocol for safely creating, publishing, releasing, auditing, and maintaining GitHub repositories: check local rules and locks, create .gitignore before the first add, run privacy checks, prepare README/i18n/banner/metadata, verify release tags and GitHub releases, and update organization profiles, llms.txt files…
release-notes
Generate changelog entries and GitHub releases from git history. Categorizes commits into features, fixes, breaking changes, and docs. Supports conventional commits, PR-based grouping, and semantic versioning. Creates formatted CHANGELOG.md entries and GitHub releases.
github-cli
Apply when using the gh CLI to manage pull requests, issues, releases, or CI workflows on GitHub.
git-conventions
Apply when committing, branching, or opening a pull request. Conventional commit format, branch naming, PR scope.
changelog-generator
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.