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 agentmods add skills/cvander/maya/schedule_draftnpx skills add cvander/Maya --skill schedule_draftgit clone --depth 1 https://github.com/cvander/MayaWhat 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 | $0.00014 | $0.00365 |
| Opus 5 | $0.00007 | $0.00182 |
| Sonnet 5 | $0.00003 | $0.00073 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
schedule-draft 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 2d 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
Schedule Draft
Generate a draft weekly schedule based on staff availability, max hours, and certifications. Flags labor law concerns including CA overtime rules, SF predictive scheduling ordinance, and missing RBS certifications.
When to Use
- When creating next week's schedule
- When checking labor law compliance for a proposed schedule
- Before publishing a new schedule
Procedure
python -m skills.schedule_draft --format json
python -m skills.schedule_draft --format json --week-of 2026-04-20
python -m skills.schedule_draft --format json --schedule-dir docs/schedule
Exit Codes
| Code | Meaning |
|---|---|
| 0 | OK, no labor law findings |
| 1 | Warnings present (overtime risk, missing cert, etc.) |
| 2 | Config error |
| 3 | Data error (missing staff.md) |
| 10 | Unexpected error |
Verification
- Exit code is 0 or 1
- stdout is valid JSON (with --format json)
data.shiftscontains generated schedule entriesfindingslists any labor law concerns with codes: OVERTIME_RISK, PREDICTIVE_SCHED, MISSING_CERT
What ships with it
10 files 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.
- __init__.py 0 B runs code
- __main__.py 401 B runs code
- fixtures/FIXTURES.md 207 B
- fixtures/happy_path/expected.json 2.4 KB
- fixtures/happy_path/staff.md 352 B
- fixtures/warn_case/expected.json 3.4 KB
- fixtures/warn_case/staff.md 343 B
- main.py 12 KB runs code
- manifest.toml 314 B
- test_main.py 4.1 KB runs code
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.
- 2d ago First seen · 53 lines · 14 tokens per session scan A 2ba8ae77c69f
schedule-draft is a skill published in the GitHub repository cvander/Maya (10 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 365 once invoked, about $0.0001 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.
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