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 Lingtai-AI/lingtai --skill report-templategit clone --depth 1 https://github.com/Lingtai-AI/lingtaiWrote 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/lingtai-ai/lingtai/report-template)<a href="https://agentmods.dev/skills/lingtai-ai/lingtai/report-template"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/report-template/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/lingtai-ai/lingtai/report-template"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/report-template.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 Rogue Agent · line 74 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00070 | $0.00914 |
| Opus 5 | $0.00035 | $0.00457 |
| Sonnet 5 | $0.00014 | $0.00183 |
| Haiku 4.5 | $0.00007 | $0.00091 |
Grade A, and why
issue-report-report-template 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 11d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue report — report template
This is a nested lingtai-issue-report reference: the canonical structure for an issue report — subject/title, body sections, and how to deliver it through the right channel before any filing decision.
The report template
Send the report as a mail message with a clear subject and a structured body. Use this skeleton:
Subject: [Issue Report] <one-line summary>
## What's wrong
<concise statement of the problem — one paragraph>
## Where
- Component: <skill name / capability name / preset name / procedure section>
- File or URL (if known): <path or URL>
## Reproduction
<exact steps you took, exact tool calls, exact responses you got. Include
verbatim error messages, status codes, or contradictory text.>
## What you expected
<what the docs/skill led you to expect>
## What actually happened
<what you observed instead>
## Severity
<one of: blocking | major | minor | cosmetic>
- blocking — agents cannot complete the affected workflow at all
- major — a documented feature is broken or absent; workaround exists but costs time
- minor — incorrect detail; doesn't break workflows but misleads new agents
- cosmetic — typo, formatting, broken link in a doc
## Suggested fix (optional)
<if you have a concrete suggestion, include it. otherwise omit this section.>
Keep the section headers verbatim — they double as the GitHub-flavored markdown issue body later, and GFM renders them cleanly. The title used for filing is your Subject line minus the [Issue Report] prefix.
Send it through the right channel first
Before any filing decision, send the report so there is a durable record and your parent/human can see it. Use the channel they are actually using:
# Internal LingTai email / peer mail
email(action="send", address=<parent_or_human_address>, subject="[Issue Report] ...", message=<body>)
# If the human is currently on Telegram/another chat channel, send or reply there instead.
# Always follow the surrounding agent's channel discipline.
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.
- 11d ago First seen · 78 lines · 70 tokens per session scan A 3c7e3f66de7c
issue-report-report-template is a skill published in the GitHub repository Lingtai-AI/lingtai (673 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 914 once invoked, about $0.0003 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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