CLI Agent Orchestrator is a tool that coordinates multiple AI coding command-line programs by running them as separate workers in isolated terminal sessions. A supervisor uses it to delegate software tasks to specialist agents in parallel or in sequence while the workers retain their normal command-line capabilities. The catalogue skills operate this orchestration workflow.
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 awslabs/cli-agent-orchestrator --skill python-review-checklistgit clone --depth 1 https://github.com/awslabs/cli-agent-orchestratorWrote 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/awslabs/cli-agent-orchestrator/python-review-checklist)<a href="https://agentmods.dev/skills/awslabs/cli-agent-orchestrator/python-review-checklist"><img src="https://agentmods.dev/badge/skills/awslabs/cli-agent-orchestrator/python-review-checklist/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/awslabs/cli-agent-orchestrator/python-review-checklist"><img src="https://agentmods.dev/badge/skills/awslabs/cli-agent-orchestrator/python-review-checklist.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.00242 |
| Opus 5.5 | $0.00008 | $0.00097 |
| Sonnet 5.5 | $0.00004 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
python-review-checklist 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 today.
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
Python Review Checklist
Apply every item below, in order, when reviewing Python code. Each item targets
one class of defect, and the example's review target (fixture/sample_note.md)
contains exactly one instance of each.
- Missing imports — every name used at module or function scope is imported.
- Mutable default arguments — no
def f(x=[])ordef f(x={}); default toNoneand assign a fresh container inside the function. - Bare
except:clauses — every handler catches a specific exception type. - Type hints — every public function annotates its parameters and return value.
Output contract
End every review with exactly one line, and nothing after it:
Checklist applied: <applied>/<total> items
<applied> counts the checklist items the review actually checked. A reviewer
that did not apply the full checklist must not print this line, so anything
downstream can treat the line as proof that this skill's guidance engaged.
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.
- today First seen · 28 lines · 20 tokens per session scan A bc9620545a6e
python-review-checklist is a skill published in the GitHub repository awslabs/cli-agent-orchestrator (1,458 stars, last pushed today), licensed Apache-2.0. It adds 20 tokens to every session and 242 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-22.
Other skills, from other repositories
python-conventions
Python style and structure conventions based on PEP 8. Load before implementing or reviewing any pyproject.toml/requirements.txt-based feature.
review
Run a structured, read-only code review through agent-rack's agentreview tool.
review-handling
Internal guidance for presenting agent-rack's agentreview output back to the user. Use whenever an agentreview call (foreground or via agentsessionstatus) returns a result.
python-anti-patterns
Use this skill when reviewing Python code for common anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.
python-code-style
Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.
agent-framework-azure-ai-py
Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.