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 filing-flowgit 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/filing-flow)<a href="https://agentmods.dev/skills/lingtai-ai/lingtai/filing-flow"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/filing-flow/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/filing-flow"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/filing-flow.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 Privilege Escalation · line 30 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00071 | $0.01761 |
| Opus 5 | $0.00036 | $0.00881 |
| Sonnet 5 | $0.00014 | $0.00352 |
| Haiku 4.5 | $0.00007 | $0.00176 |
Grade A, and why
issue-report-filing-flow 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue report — filing flow
This is a nested lingtai-issue-report reference. It governs everything after the report is drafted: human consent, detecting whether gh can file directly, the two filing paths, and proactive surfacing.
The boundary — permission required, always
You never open a GitHub issue without an explicit "yes" from the human. The human is the accountable owner of what gets filed under their name. Even if gh is authenticated and you have a shell, the per-issue consent is non-negotiable. Your role is to:
- Assemble a structured report (see the
report-templatereference) - Send the report through the appropriate channel to your parent avatar (if you're an avatar) AND to the human
- Check whether
ghis available and authenticated (see "Filing path" below) - Ask the human's permission, naming the path you'd take (direct
ghfiling vs. paste-into-browser) - Only then act — file it via
ghif they say yes, or hand them the title/body if they prefer to file manually
If the human declines, drop it. Don't nag, don't auto-retry on the next turn. Their call.
Filing path — detect gh first
Before you ask the human for permission, run a quick read-only probe to see whether the GitHub CLI is installed AND there's a way to authenticate. There are two acceptable auth sources — either is enough to make Path A available:
- Existing
gh auth— the host already has a logged-in account. - A
GH_TOKENthe human provided this session — they pasted a personal access token into chat (or it's already in your shell env).ghreadsGH_TOKENfrom the environment per-invocation, so nogh auth loginis needed.
Probe:
# Is gh installed?
command -v gh
# Is gh already authenticated?
gh auth status 2>&1
Interpret: gh installed and either auth source present → Path A is available. gh missing, or neither source present → Path A is out; fall through to Path B.
Do not run gh issue create during the probe. Do not echo, log, or commit the token. The probe is read-only; the actual filing happens only after the human says yes.
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 · 111 lines · 71 tokens per session scan A 3ebabc140816
issue-report-filing-flow is a skill published in the GitHub repository Lingtai-AI/lingtai (700 stars, last pushed today), licensed Apache-2.0. It adds 71 tokens to every session and 1,761 once invoked, about $0.0004 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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