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/anivaryam/anivaryam-plugins/httpgit clone --depth 1 https://github.com/anivaryam/anivaryam-pluginsWrote 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/anivaryam/anivaryam-plugins/http)<a href="https://agentmods.dev/commands/anivaryam/anivaryam-plugins/http"><img src="https://agentmods.dev/badge/commands/anivaryam/anivaryam-plugins/http.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 | $0.00018 | $0.00321 |
| Opus 5 | $0.00009 | $0.00161 |
| Sonnet 5 | $0.00004 | $0.00064 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
http 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.
After running, print the public URL, confirm it's reachable with `curl -sf <url>`, and if `--silent` was used, verify with `tunnel daemon status --name <name>` (or `--port N --mode http` if no name was given). What it actually says
Run tunnel http $ARGUMENTS.
Before running:
- Verify config exists at
~/.tunnel/config.yml(or runtunnel config show). If absent, walk the user throughtunnel config set-server/set-tokenfirst. - Run
tunnel doctorif this is the first invocation in the session — it catches bad URLs, unreachable relays, and missing tokens cheaply. - If
--silentis in args and the tunnel will be started inside a proc-compose stack, abort and explain —--silentdaemonizes and exits, which proc-compose treats as a crash. Use thetrapforeground pattern instead. - If
--nameis in args, confirm it satisfies[a-z0-9-]{1,32}(no leading/trailing hyphen) and isn't in the relay's reserved-name list (dashboard,metrics,mail,login,app,docs,status,staging,prod, etc.).
After running, print the public URL, confirm it's reachable with curl -sf <url>, and if --silent was used, verify with tunnel daemon status --name <name> (or --port N --mode http if no name was given).
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 · 16 lines · 18 tokens per session scan A aaa47424b799
http is a command published in the GitHub repository anivaryam/anivaryam-plugins (2 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 321 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
deploy
Build, test, deploy with staged rollout.
deploy
Deploy a frontend (React, Next.js, or static HTML) to a live URL on Butterbase.
cf-scaffold-project
Scaffold a Cloudflare project — Worker, Pages, or Worker+D1+R2 starter — with Wrangler config, Terraform skeleton, and GitHub Actions deploy using scoped API tokens.
overview
Unified cost dashboard combining state, plan, actual costs, projected costs, drift, and recommendations.
scan
Scan AWS account for cost optimization.
finops-feedback
Step 5 (Feedback Loop & Celebration) — measure realized against projected savings, compute a labelled Cloud Entropy proxy, close the opportunity, and emit at least one new idea or policy update so the loop actually closes. Applies the double-loop gate. Mutates on the closure path.