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 CyrilLeMat/temper-skills --skill parkinggit clone --depth 1 https://github.com/CyrilLeMat/temper-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/cyrillemat/temper-skills/parking)<a href="https://agentmods.dev/skills/cyrillemat/temper-skills/parking"><img src="https://agentmods.dev/badge/skills/cyrillemat/temper-skills/parking/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/cyrillemat/temper-skills/parking"><img src="https://agentmods.dev/badge/skills/cyrillemat/temper-skills/parking.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 | $0.00084 | $0.00529 |
| Opus 5 | $0.00042 | $0.00264 |
| Sonnet 5 | $0.00017 | $0.00106 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
parking 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.
What it actually says
can_i_park — skill (tempered by temper-skills)
You are an assistant.
The decision is frozen. Do not re-derive it from prose or your own judgment — the routing logic now lives in a deterministic decision tree (can_i_park.can_i_park, zero LLM calls, reviewed and version-controlled). Your job is the part the tree cannot do: turn the request into structured features, call the tree, and phrase its verdict.
How to answer
-
Extract these structured features from the request:
zone_typedayhouris_public_holidayhas_resident_permit
-
Call the decision tree and treat its result as authoritative (bundled at
scripts/can_i_park.py):from scripts.can_i_park import can_i_park verdict = can_i_park({"zone_type": zone_type, "day": day, "hour": hour, "is_public_holiday": is_public_holiday, "has_resident_permit": has_resident_permit}) -
Relay
verdictto the user. Do not override it. If a feature can't be extracted, pass it asNone— the tree is built to fall through safely.
Gray zones to surface
The tree flags these as underdetermined — mention the caveat when the answer touches them:
- (n2) Suspended on public holidays (is_public_holiday true falls through). Window is the clock hours 11 and 12 (>=11 and <13).
- (n3) The 2-hour cap can't be enforced by the tree alone; a downstream system must track elapsed duration.
Generated by temper-skills from the original skill · 2026-07-01T12:45:19Z · model: claude-sonnet-4-6 via temper-skills. The decision logic is now testable (temper-skills validate) and evolvable (temper-skills incremental) — regenerate this skill when the tree changes.
What ships with it
5 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.
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 · 36 lines · 84 tokens per session scan A 8fc70e59b6c9
parking is a skill published in the GitHub repository CyrilLeMat/temper-skills (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 529 once invoked, about $0.0004 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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