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 avivsinai/skills-marketplace --skill shaongit clone --depth 1 https://github.com/avivsinai/skills-marketplaceWrote 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/avivsinai/skills-marketplace/shaon)<a href="https://agentmods.dev/skills/avivsinai/skills-marketplace/shaon"><img src="https://agentmods.dev/badge/skills/avivsinai/skills-marketplace/shaon/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/avivsinai/skills-marketplace/shaon"><img src="https://agentmods.dev/badge/skills/avivsinai/skills-marketplace/shaon.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 | $0.00022 | $0.00678 |
| Opus 5.5 | $0.00009 | $0.00271 |
| Sonnet 5.5 | $0.00004 | $0.00136 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
shaon 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.
This is a copy
100% identical to shaon — 2 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shaon
Use the MCP tool when it covers the requested operation. Use the shaon CLI
for unsupported operations, diagnosis, or when the user asks for the CLI.
Inspect shaon --help or the relevant subcommand help for exact flags.
Choose the task
- Month status, missing days, and errors: start with
shaon attendance overview. - Daily or monthly attendance details: use
shaon attendanceread commands. - Corrections: preview the relevant
attendance reportorattendance resolvecommand first. - Payslips and salary: use
shaon payrollcommands. - Authentication or account setup: use
shaon authcommands.
Prefer structured output when another tool will consume the result. Do not request credentials or a browser login for a read until the command reports that authentication is required.
Human-attested writes
Attendance submissions are claims about real work performed. The user must attest the facts; neither inferred calendar events nor an agent's judgment is enough.
- Reporting commands preview by default. Show the employee, date or range, times, report type, and resulting action.
- Run with
--execute(or MCPexecute: true) only after the user explicitly authorizes that concrete submission. - Never autonomously rerun a write with
--execute. - After an ambiguous timeout or transport error, read back attendance state before proposing another submission.
- CAPTCHA and attended login steps must be completed by the user.
Example safe flow:
shaon attendance overview --month 2026-09
shaon attendance report day 2026-09-03 --type regular --hours 09:00-17:30
# Only after the user confirms that preview:
shaon attendance report day 2026-09-03 --type regular --hours 09:00-17:30 --execute
Use shaon attendance report range --help before a range correction; resolve
weekends, holidays, leave, and partial days instead of assuming identical work
hours for every date.
Range reports and auto-fill skip Friday and Saturday unless explicitly overridden. Auto-fill is capped at 10 days by default; use its help before changing that limit.
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.
- 1mo ago Changed · -116 lines · -65 tokens per session 2bd0d75493ab
- 2mo ago First seen · 193 lines · 87 tokens per session scan A 0f1af9305c23
shaon is a skill published in the GitHub repository avivsinai/skills-marketplace (2 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 678 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to shaon, differing in 2 lines, and is treated as a copy.
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