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 agentmods add commands/rohanmistry231/claude-code-project-structure-learning-repository/deploygit clone --depth 1 https://github.com/rohanmistry231/Claude-Code-Project-Structure-Learning-RepositoryWrote 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/rohanmistry231/claude-code-project-structure-learning-repository/deploy)<a href="https://agentmods.dev/commands/rohanmistry231/claude-code-project-structure-learning-repository/deploy"><img src="https://agentmods.dev/badge/commands/rohanmistry231/claude-code-project-structure-learning-repository/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 | $0.00000 | $0.00672 |
| Opus 5 | $0.00000 | $0.00336 |
| Sonnet 5 | $0.00000 | $0.00134 |
| Haiku 4.5 | $0.00000 | $0.00067 |
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 3d 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 https://<target-host>/health How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/deploy
Deploy the Blog API to the target environment.
Usage
/deploy [environment]
environment— one ofstagingorproduction(default:staging)
What this command does
When the user runs /deploy or /deploy staging or /deploy production,
execute the following steps in order. Stop and report if any step fails.
Step 1 — Pre-flight checks
Run these checks before touching anything. If any fail, abort and tell the user what failed:
# 1a. Make sure the working tree is clean
git status --porcelain
# Expected: no output. If there is output, say "Uncommitted changes found — commit or stash first."
# 1b. Make sure we're on the right branch
git branch --show-current
# Expected: "main" for production, any branch for staging.
# 1c. Run the full test suite
pytest arc/tests/ -v --tb=short
# Expected: 0 failures. Do not deploy if tests fail.
# 1d. Run the linter
ruff check arc/
# Expected: exit code 0.
Step 2 — Build
# Build a deployable package (wheel)
pip install build
python -m build --wheel
The wheel will appear in dist/. Note the filename for Step 3.
Step 3 — Deploy
For staging:
# Push the wheel to the staging server via scp, then restart the service
scp dist/*.whl [email protected]:/opt/blog-api/
ssh [email protected] "
cd /opt/blog-api &&
pip install --force-reinstall *.whl &&
systemctl restart blog-api
"
For production:
# Same as staging but target production server
# IMPORTANT: always confirm with the user before running this block
scp dist/*.whl [email protected]:/opt/blog-api/
ssh [email protected] "
cd /opt/blog-api &&
pip install --force-reinstall *.whl &&
systemctl restart blog-api
"
Always ask the user to confirm before deploying to production. Say: "Ready to deploy vX.Y.Z to PRODUCTION. This will affect live users. Confirm? (yes/no)"
Step 4 — Post-deploy smoke test
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.
- 3d ago First seen · 110 lines · 0 tokens per session scan A c1e5c2519ecb
deploy is a command published in the GitHub repository rohanmistry231/Claude-Code-Project-Structure-Learning-Repository (2 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 672 tokens. 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 2026-08-31.
Other commands, from other repositories
monitor
Monitor GitHub Actions CI status for the current branch. If any workflow fails, diagnose the failure, fix it, commit, push, and re-monitor — up to 3 cycles.
pm-status
Scan open PRs, report pipeline state, merge ready work to dev, and keep the staging promotion PR current.
domains
Apply the CLI runtime and safety contract before executing a command. Runtime --help is authoritative.
go-review
Go code review for idiomatic patterns.
cost-tracker
Track session costs, understand token spend, and get optimization tips.
test
Run all PandaFilter verification steps in order. Stop and report on first failure. This is the required pre-commit gate.