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 EthanYoQ/Skill-hub --skill qq-email-ground-truthgit clone --depth 1 https://github.com/EthanYoQ/Skill-hubWrote 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/ethanyoq/skill-hub/qq-email-ground-truth)<a href="https://agentmods.dev/skills/ethanyoq/skill-hub/qq-email-ground-truth"><img src="https://agentmods.dev/badge/skills/ethanyoq/skill-hub/qq-email-ground-truth/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/ethanyoq/skill-hub/qq-email-ground-truth"><img src="https://agentmods.dev/badge/skills/ethanyoq/skill-hub/qq-email-ground-truth.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00071 | $0.00450 |
| Opus 5 | $0.00036 | $0.00225 |
| Sonnet 5 | $0.00014 | $0.00090 |
| Haiku 4.5 | $0.00007 | $0.00045 |
Grade A, and why
qq-email-ground-truth 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.
What it actually says
QQ Email Ground Truth
Use this project-level skill for QQ mailbox ground truth work in this repository.
Read references/workflow.md and references/pitfalls.md first. Read references/case-study-qq-20260201-20260311.md and references/project-artifacts.md when you need a validated example, current artifact paths, or prior evidence.
Hard Boundaries
- Treat this as a project-local skill, not a global mailbox skill.
- Treat the current case-study counts, type distribution, and mail IDs as one validated example only. Do not reuse them as fixed thresholds for future QQ runs.
- Treat the currently known reimbursable types as a reference range, not a closed list. If a new type, provider, attachment pattern, or procurement scenario appears, send it to review instead of auto-excluding it.
- Reuse
build_truth_dataset.pyandaudit_email_truth.py. Do not create a parallel truth-building flow unless the user explicitly asks for one.
Required Workflow
- Confirm the mailbox account, mailbox folder, and time window.
- Follow
references/workflow.mdfor the build and validation sequence. - Use
references/pitfalls.mdas the default debug checklist when counts or fields look wrong. - Use
references/case-study-qq-20260201-20260311.mdonly as a worked example and evidence sample. - Use
references/project-artifacts.mdto find the current canonical manifests, reports, and diagnostics.
Output Expectations
- Prefer
truth_manifest.jsonfor machine comparison. - Prefer
ground_truth_report.mdfor human review. - Require
pending_review_count = 0before calling a dataset final. - Keep excluded-email and excluded-document audit trails instead of silently dropping evidence.
What ships with it
5 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.
- 11d ago First seen · 33 lines · 71 tokens per session scan A 5294e07ed36b
qq-email-ground-truth is a skill published in the GitHub repository EthanYoQ/Skill-hub (9 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 450 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 2026-08-31.
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