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 OneWave-AI/open-agent-stack --skill call-prepgit clone --depth 1 https://github.com/OneWave-AI/open-agent-stackWrote 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/onewave-ai/open-agent-stack/call-prep)<a href="https://agentmods.dev/skills/onewave-ai/open-agent-stack/call-prep"><img src="https://agentmods.dev/badge/skills/onewave-ai/open-agent-stack/call-prep/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/onewave-ai/open-agent-stack/call-prep"><img src="https://agentmods.dev/badge/skills/onewave-ai/open-agent-stack/call-prep.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 | $0.00044 | $0.00410 |
| Opus 5.5 | $0.00018 | $0.00164 |
| Sonnet 5.5 | $0.00009 | $0.00082 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
call-prep 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 1mo 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
Call Prep
Walk in knowing more than the other side expects. Input: company name and meeting context (first call, demo, negotiation, renewal); attendee names/LinkedIn URLs if known; anything from the CRM or email thread history available.
Workflow
- Research the company. Web-search recent news, funding, leadership changes, hiring signals (what roles they are posting reveals priorities), and their own positioning language. Find the thing that changed recently -- meetings exist because something changed.
- Read the attendees. Role, tenure, likely care-abouts by function (a CFO hears risk and payback; an ops lead hears hours saved). Note shared ground if it is real; skip manufactured rapport.
- Pull the history. From CRM/email/notes provided: every prior touch, what was promised, open threads, and anything they told us before -- asking a question they already answered costs credibility.
- Write the brief, one page: why this meeting is happening (their trigger, not our pipeline stage), 5-7 discovery questions sequenced from situation to pain to stakes -- specific to their business, not a generic SPIN list; the 3 objections most likely for this profile, each with an honest answer; the single realistic goal for the call and the specific next step to propose before hanging up.
Rules
- Every discovery question must be un-Googleable -- if the answer is on their website, asking it burns the meeting.
- Objection answers are honest, including "that's a real limitation, here's the trade" where true.
- One goal per call. A brief with four goals produces a call with none.
- Flag what you could not verify; a brief with a wrong fact is worse than a gap.
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.
- 1mo ago First seen · 23 lines · 44 tokens per session scan A f74b40545042
call-prep is a skill published in the GitHub repository OneWave-AI/open-agent-stack (5 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 410 once invoked, about $0.0002 per session on Opus 5.5. 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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