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 agentmods add skills/syy12335/environment-runtime/functestnpx skills add syy12335/Environment-Runtime --skill functestgit clone --depth 1 https://github.com/syy12335/Environment-RuntimeWrote 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/syy12335/environment-runtime/functest)<a href="https://agentmods.dev/skills/syy12335/environment-runtime/functest"><img src="https://agentmods.dev/badge/skills/syy12335/environment-runtime/functest.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00357 |
| Opus 5 | $0.00012 | $0.00179 |
| Sonnet 5 | $0.00005 | $0.00071 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
functest 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.
What it actually says
Functest Workflow Type
定位
functest用于生成“功能测试目标（target）”。- controller 负责确定：本轮测什么、围绕什么测、重点朝哪个方向测。
- 该 type 命中后会直接进入 workflow，不再交给 executor agent loop。
场景步骤模板
- 明确对象的直接功能测试：直接
generate_task(functest)。 - 带关注点的功能测试：把用户显式关注点写入
task_content。 - 基于失败点复测：可使用
previous_failed_track {}补全事实后generate_task(functest)。 - 对象不明确：必要时
build_context_view后再生成任务。
生成原则
task_content是当前任务 target，不是完整执行配置。- 写清测试对象、本轮目标、必要关注方向。
- 对“对象明确、任务类型明确”的请求，不得默认继续 observe。
Workflow I/O
- 入口：
scripts/run.py - 调用：
run(*, task_content: str) -> dict - 返回：
{"task_status": "done|failed", "task_result": "..."}
What ships with it
1 file 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.
- 4d ago First seen · 38 lines · 23 tokens per session scan A d894dbfec7a7
functest is a skill published in the GitHub repository syy12335/Environment-Runtime (127 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 357 once invoked, about $0.0001 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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