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 mindspore-ai/akg --skill hint-modegit clone --depth 1 https://github.com/mindspore-ai/akgWrote 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/mindspore-ai/akg/hint-mode)<a href="https://agentmods.dev/skills/mindspore-ai/akg/hint-mode"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/hint-mode/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/mindspore-ai/akg/hint-mode"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/hint-mode.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 | $0.00033 | $0.01269 |
| Opus 5 | $0.00016 | $0.00634 |
| Sonnet 5 | $0.00007 | $0.00254 |
| Haiku 4.5 | $0.00003 | $0.00127 |
Grade A, and why
hint-mode 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 9d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hint 模式:参数空间配置指南
概述
Hint 模式用于从任务描述中识别参数范围约束,生成参数空间配置(space_config),支持后续的自动调优。
Hint 语法格式
标准格式
# @hint: param in [val1, val2, ...] → type='choice', values=[...]
# @hint: param in range(min, max, step=N) → type='range', min=..., max=..., step=...
# @hint: param = value → type='fixed', value=...
# @hint: param in pow2(min_pow, max_pow) → type='power_of_2', min_pow=..., max_pow=...
# @hint: param in pow of 2 → type='power_of_2'
兼容格式
# @range_hint("param", start=min, end=max) → type='range', min=..., max=...
# @elemwise_hint("param", [val1, val2]) → type='choice', values=[...]
# @elem_hint("param", [val1, val2]) → type='choice', values=[...]
示例
# @hint: batch_size in pow of 2 → {'type': 'power_of_2', 'min_pow': 3, 'max_pow': 6} # [8, 16, 32, 64]
# @hint: dim in range(16, 65536) → {'type': 'range', 'min': 16, 'max': 65536, 'step': 1}
# @hint: BLOCK_M in [64, 128, 256] → {'type': 'choice', 'values': [64, 128, 256]}
Hint 提取规则
- 识别所有 hint:包括被注释掉的 hint(
# @range_hint),都应识别并提取 - 完整提取:如果有多个 hint,必须全部提取,不能遗漏
- 格式转换:
- 装饰器格式(如
@range_hint("param", st=8, ed=64))→ 提取括号内信息 - 注释格式(如
# @hint: param in range(16, 65536))→ 提取冒号后声明 - 统一转换为标准的
SPACE_CONFIG字典格式
- 装饰器格式(如
参数空间配置模板
"""参数空间配置"""
import torch # 或 import mindspore as ms
# ===== 参数空间定义 =====
SPACE_CONFIG = {
'param1': {'type': 'choice', 'values': [val1, val2, ...]},
'param2': {'type': 'range', 'min': min_val, 'max': max_val, 'step': step_val},
'param3': {'type': 'power_of_2', 'min_pow': min_exp, 'max_pow': max_exp},
# ... 根据 hint 提取的所有参数
}
# ===== 元信息 =====
META_INFO = {
'op_name': 'op_name',
'framework': 'torch', # 或 'mindspore'
'param_names': ['param1', 'param2', ...] # 参数名列表,保持顺序!
}
# ===== 输入构造函数 =====
def create_inputs(param1, param2, ...):
"""
根据参数生成输入
参数顺序必须与 META_INFO['param_names'] 一致
"""
...
return [tensor1, tensor2, ...]
# ===== 初始化输入函数(可选)=====
def get_init_inputs():
"""如果原始代码有此函数,完整复制"""
return [] # 或 ["auto"]
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.
- 9d ago First seen · 122 lines · 33 tokens per session scan A 79f9b5a11625
hint-mode is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 29d ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,269 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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