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 jonny-1812/corebee-mcp-skills --skill weekly-reportgit clone --depth 1 https://github.com/jonny-1812/corebee-mcp-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/jonny-1812/corebee-mcp-skills/weekly-report)<a href="https://agentmods.dev/skills/jonny-1812/corebee-mcp-skills/weekly-report"><img src="https://agentmods.dev/badge/skills/jonny-1812/corebee-mcp-skills/weekly-report/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/jonny-1812/corebee-mcp-skills/weekly-report"><img src="https://agentmods.dev/badge/skills/jonny-1812/corebee-mcp-skills/weekly-report.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 | $0.00058 | $0.01481 |
| Opus 5 | $0.00029 | $0.00740 |
| Sonnet 5 | $0.00012 | $0.00296 |
| Haiku 4.5 | $0.00006 | $0.00148 |
Grade A, and why
weekly-report 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 12d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Support Report
Generate a complete support operations snapshot by combining data from multiple analytics tools.
Workflow Modes
Current Period (default)
Generates a full report for a single time period.
- Determine the period from the user's request. Default:
this_week. Supported values:this_week,last_week,this_month,last_month,last_7_days,last_30_days. - Fetch dashboard KPIs using
get_metricswith the resolved period - Fetch team performance using
get_agent_performancewith the same period - Fetch channel breakdown using
get_channel_analyticswith the same period - Fetch conversation trends using
get_trendswithmetric: "conversations"and the period - Fetch AI automation trends using
get_trendswithmetric: "ai_responses"and the period - Compile and present the full report
Comparison Mode
Compares two periods side by side with delta calculations showing improvement or regression.
- Determine the two periods (e.g.,
this_weekvslast_week, orthis_monthvslast_month) - Fetch all data for both periods (KPIs, team performance, channels, trends)
- Calculate deltas for each metric: absolute change and percentage change
- Flag metrics that improved with an up arrow and metrics that regressed with a down arrow
- Present the comparison table with both periods and the delta column
Executive Summary
A condensed version for leadership — key numbers, top-line trends, and action items only. No detailed tables.
- Fetch dashboard KPIs using
get_metricswith the resolved period - Fetch team performance using
get_agent_performance(top 3 performers only) - Fetch conversation trends using
get_trendswithmetric: "conversations" - Present a 5-8 line summary with: total volume, resolution rate, average response time, AI automation rate, top performer, and one key insight or action item
Report Structure
Support Operations — Weekly Report
Overview ([Period])
- Open conversations: [count]
- Resolved this period: [count]
- New contacts: [count]
- Total messages: [count]
- AI-handled responses: [count] ([percentage]% automation rate)
- Avg first response time: [duration]
- Avg resolution time: [duration]
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.
- 12d ago First seen · 127 lines · 58 tokens per session scan A d7a2ff71cf26
weekly-report is a skill published in the GitHub repository jonny-1812/corebee-mcp-skills (0 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,481 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 2026-08-30.
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