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 adampoit/ai --skill khalgit clone --depth 1 https://github.com/adampoit/aiWrote 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/adampoit/ai/khal)<a href="https://agentmods.dev/skills/adampoit/ai/khal"><img src="https://agentmods.dev/badge/skills/adampoit/ai/khal/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/adampoit/ai/khal"><img src="https://agentmods.dev/badge/skills/adampoit/ai/khal.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 | $0.00031 | $0.00389 |
| Opus 5.5 | $0.00012 | $0.00156 |
| Sonnet 5.5 | $0.00006 | $0.00078 |
| Haiku 4.5 | $0.00003 | $0.00039 |
Grade A, and why
khal 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.
What it actually says
Khal
Read calendar events from the terminal with khal.
khal list --format '{calendar}|{start}|{end}|{title}|{location}|{description}|{status}' today eod
List Events
Today's events:
khal list --format '{calendar}|{start}|{end}|{title}|{location}|{description}|{status}' today eod
Next 7 days:
khal list --format '{calendar}|{start}|{end}|{title}|{location}|{description}|{status}' today 7d
Custom range:
khal list --format '{calendar}|{start}|{end}|{title}|{location}|{description}|{status}' "start-date" "end-date"
Common date examples: now, today, tomorrow, eod, 7d, 2026-02-21.
Search Events
khal does not provide a native full-text search command.
Use a wide date range and filter results in your response:
khal list --format '{calendar}|{start}|{end}|{title}|{location}|{description}|{status}' today 365d
Filter by keyword in title, description, or location after collecting the output.
Parsing Notes
- Event rows use
|separators in the format above khalmay print date header lines (for exampleMonday, 2026-02-23); treat those as section headers, not events- Return at most the number of events requested by the user
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 First seen · 53 lines · 31 tokens per session scan A 2a1de9c798f1
khal is a skill published in the GitHub repository adampoit/ai (2 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 389 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
ai-context-primer
Build the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, my AI results are…
get-more-from-ai
Level up how you actually use AI — from basic one-shot questions to the techniques that get dramatically better results — matched to what you already do. Use when asked how do I get better at using AI, how do power users use AI, I feel like I'm using AI at 10%, or teach me to use AI better. Produces an honest read of…
prompt-debugging
Figure out why a prompt isn't working and fix it — diagnose the actual failure (ambiguity, missing context, wrong format, conflicting instructions) instead of randomly rewording. Use when asked why isn't my prompt working, the AI keeps ignoring my instructions, my prompt gives inconsistent results, or how do I fix…
prompt-library-builder
Build a personal library of reusable prompts for the things you ask AI again and again — so you stop rewriting the same request from scratch. Use when asked help me build a prompt library, save my best prompts, I keep writing the same prompts, or organize my AI prompts. Produces a captured set of your recurring AI…
prompt-optimizer
Diagnose and rewrite an underperforming LLM prompt so it produces reliable, well-structured output. Use when asked to improve a prompt, fix a prompt that gives inconsistent or wrong results, reduce hallucination/refusals, or make output follow a format. Produces a rewritten prompt with a diagnosis of what was failing…
a0-development
Develop or operate Agent Zero: projects, chats, tasks, framework, tools and API/WebUI.