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 sun2443/designer-skills --skill weekly-prep-briefgit clone --depth 1 https://github.com/sun2443/designer-skillsWrote 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/sun2443/designer-skills/weekly-prep-brief)<a href="https://agentmods.dev/skills/sun2443/designer-skills/weekly-prep-brief"><img src="https://agentmods.dev/badge/skills/sun2443/designer-skills/weekly-prep-brief/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/sun2443/designer-skills/weekly-prep-brief"><img src="https://agentmods.dev/badge/skills/sun2443/designer-skills/weekly-prep-brief.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 | $0.01152 |
| Opus 5.5 | $0.00022 | $0.00461 |
| Sonnet 5.5 | $0.00011 | $0.00230 |
| Haiku 4.5 | $0.00005 | $0.00115 |
Grade A, and why
weekly-prep-brief 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 13d 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.
This is a copy
100% identical to weekly-prep-brief — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Prep Brief
Generate a single comprehensive weekly briefing that covers every external customer or prospect call in the next 7 days, with per-meeting account and contact research from Common Room.
Briefing Process
Step 1: Get the Week's External Meetings
Option A — Calendar connected:
Use the ~~calendar connector to fetch all meetings scheduled in the next 7 days (or a user-specified range). Filter to keep only external meetings — those with attendees from outside your organization. Discard internal-only meetings, one-on-ones with colleagues, and recurring internal syncs.
Identify for each external meeting:
- Company name
- Meeting date and time
- External attendee names and email addresses
Option B — No calendar connected: Ask the user: "To build your weekly prep brief, I'll need your upcoming external calls. Please list them: company name, date/time, and attendee names."
Accept freeform input and parse it into a structured list before proceeding.
Step 2: Confirm the Meeting List
Present the identified meetings to the user for confirmation before beginning research:
"Here are the external calls I found for this week. Let me know if anything's missing or should be excluded:
- [Company] — [Day], [Time] — [Attendees]
- ..."
This prevents wasted research on cancelled or incorrect meetings.
Step 3: Research Each Meeting
For each confirmed external meeting, run in parallel where possible:
- Account research — full account snapshot using the account-research skill
- Contact research — profile for each external attendee using the contact-research skill
Common Room data is the primary source. After CR research, run a quick recency check for each company — this is supplementary, not primary:
- Search
"[company name]" newsscoped to the last 7 days - For executive attendees, search their name for recent public posts or interviews
- Only include findings that are genuinely noteworthy (funding, leadership changes, major press). Don't pad the brief with generic news.
What ships with it
1 file 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.
- 13d ago First seen · 127 lines · 54 tokens per session scan A 3c6a45f653a6
weekly-prep-brief is a skill published in the GitHub repository sun2443/designer-skills (0 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to weekly-prep-brief, differing in 0 lines, and is treated as a copy.
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