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 TesslateAI/OpenSail --skill agent-buildergit clone --depth 1 https://github.com/TesslateAI/OpenSailWrote 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/tesslateai/opensail/agent-builder)<a href="https://agentmods.dev/skills/tesslateai/opensail/agent-builder"><img src="https://agentmods.dev/badge/skills/tesslateai/opensail/agent-builder/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/tesslateai/opensail/agent-builder"><img src="https://agentmods.dev/badge/skills/tesslateai/opensail/agent-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.01586 |
| Opus 5.5 | $0.00012 | $0.00634 |
| Sonnet 5.5 | $0.00006 | $0.00317 |
| Haiku 4.5 | $0.00003 | $0.00159 |
Grade A, and why
agent-builder 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use
Invoke this skill when the user asks you to:
- Create a new specialised agent (e.g., "build me a daily standup digester").
- Wire a schedule, webhook, or app event to an agent so it fires autonomously.
- Attach a skill or MCP server to an agent you (or the user) own.
- Request a missing capability before performing a gated action.
Do NOT invoke this skill for:
- Editing the system prompt of an already-published agent — that requires forking; the UI handles it.
- Publishing an agent to the marketplace. Publishing is a UI-only
action that flips
is_published=Trueafter a human review. There is nopublish_agenttool.
Hard rules — read before any tool call
- Depth-1 cap. You can create child agents and attach schedules
to them, but those children cannot themselves spawn grandchildren.
The
attach_scheduletool rejects depth-2 attempts with codedepth_exceeded. The DB also enforcesdepth IN (0, 1)as a second line of defence. - Drafts only. Every agent and automation you create starts in
DRAFT state:
MarketplaceAgent.is_published=False— invisible in the public marketplace.AutomationDefinition.is_active=False— never fires. The user must enable both in the UI before anything goes live.
- Positive-list inheritance. A child automation's contract MAY
only carry scopes from this list:
tools.execute,read_file,write_file,bash_exec,web_fetch,web_search,send_message,app.invoke, plus anymcp.*prefix. The non-inheritable scopes you can NOT propagate includemarketplace.authorandautomations.write—attach_schedulerejects child contracts that contain them. - Budget rollup. A child automation's
max_spend_per_run_usdmust be<=the parent's. Daily spend is debited from BOTH the child's daily counter AND every ancestor in the parent chain — if any counter would go negative the run is paused withpaused_reason='parent_budget_exhausted'. You cannot use a child to escape a parent's daily cap.
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.
- 1mo ago First seen · 150 lines · 30 tokens per session scan A 89bfe2ea252b
agent-builder is a skill published in the GitHub repository TesslateAI/OpenSail (644 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,586 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 2026-08-30.
Other skills, from other repositories
cis-aws-database-3.2
Ensure to Create The Appropriate Deployment Configuration.
llamaindex
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM…
github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management.
flow-nexus-platform
Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges.
github-workflow-automation
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management.
swarmclaw
AI agent runtime and multi-agent orchestration platform. Teaches agents how to use SwarmClaw's 6 primitive tools, persistent memory, dreaming, delegation, connectors, credentials, and the skill system. Use when an agent is running on SwarmClaw and needs to understand the platform's capabilities.