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 zeenie-ai/OpenCompany --skill subagent-skillgit clone --depth 1 https://github.com/zeenie-ai/OpenCompanyWrote 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/zeenie-ai/opencompany/subagent-skill)<a href="https://agentmods.dev/skills/zeenie-ai/opencompany/subagent-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/subagent-skill/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/zeenie-ai/opencompany/subagent-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/subagent-skill.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 | $0.00834 |
| Opus 5 | $0.00015 | $0.00417 |
| Sonnet 5 | $0.00006 | $0.00167 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
subagent-orchestration 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 4d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Durable Subagent Orchestration
Connected teammates extend the team lead's capabilities. Before declining a request, inspect the connected teammate list and match the work to an agent's label, type, and capability description.
Mandatory delegation path
All teammate work must be created with task_manager using
operation="assign_task". Never call delegate_to_* directly. The runtime
keeps those delegate identities private and uses them only after Task Manager
has authorized and persisted the assignment.
For every assignment provide:
title: short human-readable task name;mission: one bounded outcome;assignee_node_id: an exact connected teammate ID;context: only relevant inputs and constraints;acceptance_criteria: observable conditions for approval;depends_on: task IDs when sequencing is required.
Independent assign_task calls may be emitted together. All tasks persist
before execution and enter a deterministic queue. At most three descendants,
including grandchildren, run concurrently; excess work remains queued.
Once assignments return queued, tell the user work was delegated and return.
Never wait or poll for completion in the assigning invocation. A detached
durable runner continues the work and taskTrigger starts the later review.
Capability matching
Every line in the connected teammate list ends with that agent's connected
tools and skills, for example
- web_1: Web Agent (aiAgent) - tools: TikHub (Scrape TikTok, Douyin, ...); skills: tikhub-skill (...).
Match the work to those tools and skills first; the agent type is only a
fallback when the line carries no capability clause.
- Android agents: connected Android device services.
- Coding agents: implementation, code analysis, tests, and computation.
- Web agents: browsing, HTTP, extraction, and web interaction.
- Social agents: messaging and social-platform operations.
- Travel agents: location and itinerary work.
- Task agents: scheduling and task-domain operations.
- Custom
aiAgentteammates: use their visible label and description.
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.
- 4d ago Changed · +6 lines 0a276c17824d
- 12d ago First seen · 85 lines · 30 tokens per session scan A e3a0ee7dbfe2
subagent-orchestration is a skill published in the GitHub repository zeenie-ai/OpenCompany (883 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 834 once invoked, about $0.0002 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 2026-08-30.
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