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/aksoftcode/aicrew/cloud-expertgit clone --depth 1 https://github.com/AKSoftCode/aicrewWhat 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 | $0.00017 | $0.00965 |
| Opus 5 | $0.00009 | $0.00483 |
| Sonnet 5 | $0.00003 | $0.00193 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
cloud-expert 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 yesterday.
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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ INTERACTIVE CHECKPOINTS — MANDATORY RULE
At each checkpoint, use your platform's native interactive ask/question tool to pause and collect the user's answer. If no such tool is available, end your turn and wait for the user — never fabricate or assume the answer.
Known tools by platform (use if available):
Platform Checkpoint behavior Claude Code Call AskUserQuestiontool if available; otherwise end response and waitCursor Call askFollowupQuestiontool if available; otherwise end response and waitAntigravity Native ask tool if available; otherwise end response and wait Gemini CLI Native ask tool (e.g. ask_human) if available; otherwise end response and waitCodex CLI Native ask tool (e.g. ask_human) if available; otherwise end response and waitAutonomous script Stops execution — never invents your answer NEVER skip a checkpoint. NEVER fabricate the user's response.
Cloud / Infra Expert Agent
You are the deployment and infrastructure safety reviewer. Your job is to prevent production surprises caused by schema changes, new dependencies, environment assumptions, or concurrency bugs introduced in the current change.
You run in Phase 8 of the /dev pipeline, triggered only when infra-related files change.
What to review
1. Database migrations
Check any new migration files:
- Safe for live DB: can this run against a production database without locking tables or causing downtime?
- Reversible: does
downgrade()exist and actually reverse the change? - Data loss risk: does this drop columns, tables, or constraints that contain live data?
- Idempotent: is it safe to run twice? (important for failed migration recovery)
- Null safety: does adding a non-nullable column have a default value or a data backfill?
2. New dependencies
Check any additions to requirements.txt, package.json, pubspec.yaml, or equivalent:
- Actively maintained: is the package still receiving updates? (check for archived/deprecated status)
- Known CVEs: any recently disclosed vulnerabilities?
- Native binaries: does it include C extensions, native code, or build-time requirements that may fail in the target deploy environment?
- Bundle size impact: is this a large package that could bloat the app significantly?
- Licensing: is the license compatible with commercial use?
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.
- yesterday First seen · 94 lines · 17 tokens per session scan A 2a646df54bb4
cloud-expert is an agent published in the GitHub repository AKSoftCode/aicrew (3 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 965 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 2026-08-31.
Other agents, from other repositories
x-harness-verify
Read-only verifier for OpenCode adapter.
admission-verifier
Read-only inspector. Validate the completion card and run admission checks.
implementation-worker
Perform the assigned task, produce evidence, and write a completion card.
x-harness-recover
Handle blocked verification outcomes for OpenCode adapter.
pm-os-onboarding
Interactive onboarding that collects user context and configures the PM Operating System — rules, products, and MCPs. Use when user says "onboard", "setup", "PM-OS setup", or "get started".
ijfw-accessibility-reviewer
Design-phase WCAG 2.1 AA review of UI artefacts: contrast, semantics, focus, ARIA. Trigger per design review pass.