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 10xHub/agentflow-cli --skill agentflowgit clone --depth 1 https://github.com/10xHub/agentflow-cliWrote 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/10xhub/agentflow-cli/agentflow)<a href="https://agentmods.dev/skills/10xhub/agentflow-cli/agentflow"><img src="https://agentmods.dev/badge/skills/10xhub/agentflow-cli/agentflow/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/10xhub/agentflow-cli/agentflow"><img src="https://agentmods.dev/badge/skills/10xhub/agentflow-cli/agentflow.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 | $0.00149 | $0.01647 |
| Opus 5.5 | $0.00060 | $0.00659 |
| Sonnet 5.5 | $0.00030 | $0.00329 |
| Haiku 4.5 | $0.00015 | $0.00165 |
Grade A, and why
agentflow 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentflow Project Skill
Use this skill when working in an Agentflow project. Agentflow is a multi-agent framework that wraps official OpenAI and Google SDK capabilities behind a unified graph, agent, tool, state, storage, API, CLI, and TypeScript client interface.
Treat https://agentflow.10xscale.ai/ as the first source of truth for public package names, install commands, and user-facing behavior. Use implementation source after the docs establish the intended API.
Workflow
-
Identify the published package or docs surface involved:
- PyPI core Python SDK:
10xscale-agentflow(pip install 10xscale-agentflow), source at https://github.com/10xHub/Agentflow/tree/main/agentflow/agentflow - PyPI API/CLI SDK:
10xscale-agentflow-cli(pip install 10xscale-agentflow-cli), source at https://github.com/10xHub/Agentflow/tree/main/agentflow-api/agentflow_cli - npm TypeScript SDK:
@10xscale/agentflow-client(npm install @10xscale/agentflow-client), source at https://github.com/10xHub/Agentflow/tree/main/agentflow-client/src - Main docs: https://agentflow.10xscale.ai/
- Playground/UI:
agentflow playcommand after installed cli
- PyPI core Python SDK:
-
Read the matching reference file before changing behavior. Paths are relative to this skill's directory:
Core Python SDK
- Architecture and package flow:
references/architecture.md - Agent constructor, provider, reasoning, retry, fallback, output_schema:
references/agents-and-tools.md - Graph construction, nodes, edges, compile, interrupts, config keys:
references/state-graph.md - State, messages, and content blocks:
references/state-and-messages.md - Threads and checkpointing:
references/checkpointing-and-threads.md - Dependency injection (InjectQ):
references/dependency-injection.md - Multimodal files and media stores:
references/media-and-files.md - Long-term memory stores (MemoryConfig, QdrantStore, Mem0Store):
references/memory-and-store.md - Streaming, StreamChunk, SSE, ResponseGranularity:
references/streaming.md - Stream emitter for tool progress updates:
references/stream-emitter.md - Observability hooks, validators, and runtime jumps:
references/callbacks-and-command.md - Prebuilt agents (ReactAgent, PlanActReflectAgent, StructuredOutputAgent, SupervisorTeamAgent, SwarmAgent, RAGAgent) and tools:
references/prebuilt-agents-and-tools.md - Event publishers and A2A/ACP runtime protocols:
references/publishers-and-runtime-protocols.md - Context management, ID generation, and background tasks:
references/context-id-background.md - Provider internals and adapters:
references/providers-and-adapters.md - Prompt-injection and validation safety:
references/security-and-validators.md - Realtime audio-to-audio voice agents (AudioAgent, Gemini Live,
arealtime, WebSocket bridge):references/realtime.md
- Architecture and package flow:
What ships with it
33 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agents-and-tools.md 12 KB
- references/api-client.md 2.7 KB
- references/api-configuration.md 3.0 KB
- references/api-settings-and-middleware.md 3.1 KB
- references/architecture.md 4.6 KB
- references/auth-and-authorization.md 5.8 KB
- references/callbacks-and-command.md 13 KB
- references/checkpointing-and-threads.md 2.4 KB
- references/cli-commands.md 3.0 KB
- references/client-auth-and-errors.md 2.7 KB
- references/client-messages-invoke-stream.md 3.3 KB
- references/client-threads-memory-files.md 2.6 KB
- references/context-id-background.md 2.4 KB
- references/dependency-injection.md 2.0 KB
- references/evaluation.md 18 KB
- references/id-and-thread-name-generators.md 2.2 KB
- references/media-and-files.md 2.1 KB
- references/memory-and-store.md 2.4 KB
- references/prebuilt-agents-and-tools.md 13 KB
- references/production-runtime.md 2.2 KB
- references/providers-and-adapters.md 3.0 KB
- references/publishers-and-runtime-protocols.md 2.8 KB
- references/rate-limiting.md 6.0 KB
- references/realtime.md 9.5 KB
- references/remote-tools.md 1.6 KB
- references/rest-api-and-errors.md 3.4 KB
- references/security-and-validators.md 3.0 KB
- references/state-and-messages.md 2.6 KB
- references/state-graph.md 7.3 KB
- references/stream-emitter.md 3.7 KB
- references/streaming.md 1.8 KB
- references/testing-and-evaluation.md 2.5 KB
- references/unit-testing.md 6.3 KB
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 · 93 lines · 149 tokens per session scan A 4412a5d6b628
agentflow is a skill published in the GitHub repository 10xHub/agentflow-cli (5 stars, last pushed 2d ago), licensed MIT. It adds 149 tokens to every session and 1,647 once invoked, about $0.0006 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 2026-10-06.
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