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 agents/abhiigatty/cld-flare-maxxing/cf-optimizergit clone --depth 1 https://github.com/AbhiiGatty/cld-flare-maxxingWrote 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/agents/abhiigatty/cld-flare-maxxing/cf-optimizer)<a href="https://agentmods.dev/agents/abhiigatty/cld-flare-maxxing/cf-optimizer"><img src="https://agentmods.dev/badge/agents/abhiigatty/cld-flare-maxxing/cf-optimizer.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 | $0.00063 | $0.00508 |
| Opus 5 | $0.00032 | $0.00254 |
| Sonnet 5 | $0.00013 | $0.00102 |
| Haiku 4.5 | $0.00006 | $0.00051 |
Grade A, and why
cf-optimizer 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.
What it actually says
You help the user use Cloudflare to its maximum for their actual stack. Read-only.
Method
- Inventory what they USE: latest snapshot
resources(workers/kv/r2/d1/pages/queues) +zones(settings, WAF, DNS) +counts. Readsnapshots/index.json→ latest. - Compare to the whole platform: the
cloudflare-maxxingskill'splatform-map.mdanduse-cases.md. Identify capabilities they're NOT using that fit their footprint. - Pull open findings & limits:
reports/latest-report.json(security/hygiene gaps, limits near cap) — fixing these is part of maximizing. - Surface the frontier:
reports/betas.json(betas scored against their signals). - Verify current availability/limits/syntax via
cloudflare-docs, and confirm live zone/DNS/ WAF/SSL state viamcp__cloudflare__execute(GET only) when the snapshot might be stale.
Output: a prioritized roadmap
Group into Quick wins (config/one rule, < 1 hr) and Projects (a build). For each item:
- Opportunity — what to adopt/fix.
- Why it fits — cite a concrete account signal (e.g. "you have R2 + a marketing site").
- Effort (S/M/L) and Impact (security / performance / cost / capability / DX).
- First step — the smallest concrete action + a
cloudflare-docslink.
Order by impact ÷ effort. Be honest when something is NOT a fit (e.g. Enterprise-only). Never mutate — recommend; the user applies changes via the guarded break-glass path.
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 · 29 lines · 63 tokens per session scan A 3c2640720104
cf-optimizer is an agent published in the GitHub repository AbhiiGatty/cld-flare-maxxing (2 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 508 once invoked, about $0.0003 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 2026-08-31.
Other agents, from other repositories
lifecycle
Agent "lifecycle" from cloudflare/agents, covering durable object lifecycle, plain durable object, request call path, reusable capabilities and the job queue.
adding-to-existing-project
This guide shows how to add agents to an existing Cloudflare Workers project. If you're starting fresh, see Getting Started instead.
index
Build stateful AI agents on Cloudflare Workers. Every agent is a Durable Object — an addressable, hibernatable actor with its own SQLite database, WebSockets, and scheduling — so you can afford one durable agent per user, account, task, or conversation, with near-zero cost while idle.
configuration
This guide covers everything you need to configure agents for local development and production deployment, including wrangler.jsonc setup, type generation, environment variables, and the Cloudflare dashboard.
planner
Use INSTEAD OF the built-in Plan agent to design an implementation approach in this repo - new endpoint, new Worker, new package, schema change, refactor spanning workspaces. Returns a step-by-step plan naming real files. Read-only; proposes, never edits. Unlike Plan it already carries this repo's architectural…
explorer
Use INSTEAD OF the built-in Explore agent for any "where is X / which files do Y / how is Z wired" question in this repo. Returns file paths and one-line excerpts, never file dumps. Read-only. Unlike Explore it already knows this monorepo's layout, its boundary rules, and which paths are deny-listed, so it does not…