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 Gravisun/lynqu-ai-toolkit --skill lynqu-qualifygit clone --depth 1 https://github.com/Gravisun/lynqu-ai-toolkitWrote 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/gravisun/lynqu-ai-toolkit/lynqu-qualify)<a href="https://agentmods.dev/skills/gravisun/lynqu-ai-toolkit/lynqu-qualify"><img src="https://agentmods.dev/badge/skills/gravisun/lynqu-ai-toolkit/lynqu-qualify/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/gravisun/lynqu-ai-toolkit/lynqu-qualify"><img src="https://agentmods.dev/badge/skills/gravisun/lynqu-ai-toolkit/lynqu-qualify.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 | $0.00054 | $0.02053 |
| Opus 5 | $0.00027 | $0.01026 |
| Sonnet 5 | $0.00011 | $0.00411 |
| Haiku 4.5 | $0.00005 | $0.00205 |
Grade A, and why
lynqu-qualify 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 10d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 10d ago First seen · 191 lines · 54 tokens per session scan A f0412b8d9fc8
lynqu-qualify is a skill published in the GitHub repository Gravisun/lynqu-ai-toolkit (5 stars, last pushed 7d ago), with no licence file. It adds 54 tokens to every session and 2,053 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 2026-08-31.
Other skills, from other repositories
account-research
Build a sharp, one-page account brief before a call — firmographics, recent triggers, the likely buying committee, mapped pains, and hypotheses to test. Use before a discovery call, an outbound push, or any first touch with a new account. Triggers on: research this account, company research, account brief, who are…
discovery-planning
Build a discovery call plan — a hypothesis-driven question tree, a pain-to-impact-to-priority ladder, and multi-threading targets — so you walk in knowing exactly what to ask and why. Use before a discovery call or any meeting where you need to uncover problem, impact, and decision process. Triggers on: plan…
expansion-upsell
Grow an existing account — map whitespace, read expansion-readiness signals, run the land-and-expand play, and time the ask to value realization. Use when planning how to expand, upsell, or cross-sell into a current customer. Triggers on: expansion, upsell, grow this account, cross-sell, land and expand.
forecast-hygiene
Audit a pipeline forecast for category discipline, evidence, and close-date sanity, then output a cleaned, defensible forecast. Use before a forecast call or pipeline review. Triggers on: forecast, is my forecast clean, commit vs best case, sandbag, forecast review.
meddpicc-qualification
Score a deal against MEDDPICC, separate evidence from assumption on every element, and turn the gaps into specific next actions. Use to pressure-test whether a deal is real and where it's exposed. Triggers on: qualify this deal, MEDDPICC, is this real, qualification gaps, score this deal.
multithreading
Widen a deal beyond a single contact by mapping the buying committee, finding intro paths, and tailoring a value angle per role. Use when a deal is single-threaded or you need to reach more people. Triggers on: multithread, single threaded, reach more people, widen the deal, more contacts.