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 commands/chemaclass/agnostic-ai/sample-commandgit clone --depth 1 https://github.com/Chemaclass/agnostic-aiWhat 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 | $0.00011 | $0.00023 |
| Opus 5 | $0.00005 | $0.00012 |
| Sonnet 5 | $0.00002 | $0.00005 |
| Haiku 4.5 | $0.00001 | $0.00002 |
Grade A, and why
sample-command 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
Run the sample command steps.
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 · 7 lines · 11 tokens per session scan A 8153cbb3592a
sample-command is a command published in the GitHub repository Chemaclass/agnostic-ai (11 stars, last pushed 5d ago), licensed MIT. It adds 11 tokens to every session and 23 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 2026-08-30.
Other commands, from other repositories
tldr
Re-apply TLDR rules for this turn (verdict first, no filler).
tldr-help
Quick reference card for tldr modes, slash commands, and triggers.
tldr-update
Update TLDR from GitHub and refresh installed agent hooks/skills/rules.
tldr-commit
Generate tldr-style commit message (verdict first, ≤50 char subject, why over what).
tldr-compress
Compress natural language files into TLDR format to save input tokens.
tldr-review
One-line TLDR PR review comments (verdict first, no filler).