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 xobotyi/cc-foundry --skill subagent-engineeringgit clone --depth 1 https://github.com/xobotyi/cc-foundryWrote 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/xobotyi/cc-foundry/subagent-engineering)<a href="https://agentmods.dev/skills/xobotyi/cc-foundry/subagent-engineering"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/subagent-engineering/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/xobotyi/cc-foundry/subagent-engineering"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/subagent-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 79 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00035 | $0.02651 |
| Opus 5.5 | $0.00014 | $0.01060 |
| Sonnet 5.5 | $0.00007 | $0.00530 |
| Haiku 4.5 | $0.00003 | $0.00265 |
Grade A, and why
subagent-engineering 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A subagent is a separate context with its own system prompt. It inherits none of the caller's conversation, and everything it reads is discarded when it stops — only what it returns survives. Isolation is the reason to pay for one, and the return value is the entire product.
Delegate only where the isolation pays
- Delegate work whose output is far larger than its conclusion — a wide search, a long file, a verbose test run. The caller pays for the summary instead of the transcript.
- Delegate to restrict, too. A tool allowlist or a cheaper model binds the whole run, which no instruction inside the main conversation achieves.
- Keep the work in the main conversation when it needs back-and-forth, when several phases share the same context, or when the change is small and targeted. A subagent starts cold: it pays in startup latency and in rediscovering what the caller already knows.
- Write a skill instead when the artifact wanted is reusable instruction text that runs in the caller's own context. A skill carries procedure; a subagent carries a context boundary.
- A subagent runs its own system prompt; an output style modifies the main agent's. A style appends its body to the
session prompt and, under
keep-coding-instructions: false, drops the# Doing taskssection — it never gives the work a context of its own. - Check the built-ins before writing a definition —
Explorefor read-only search on Haiku,Planfor read-only research, andgeneral-purpose, which is what anAgentcall gets when it names no type. - A subagent cannot spawn a subagent. Every fan-out is decided by the caller, so an agent that discovers more work reports it rather than delegating it.
What ships with it
7 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.
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 · 162 lines · 35 tokens per session scan A 624f8945bf02
subagent-engineering is a skill published in the GitHub repository xobotyi/cc-foundry (22 stars, last pushed 7d ago), licensed MIT. It adds 35 tokens to every session and 2,651 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.
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