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 AKSoftCode/aicrew --skill aicrew-tersegit clone --depth 1 https://github.com/AKSoftCode/aicrewWrote 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/aksoftcode/aicrew/aicrew-terse)<a href="https://agentmods.dev/skills/aksoftcode/aicrew/aicrew-terse"><img src="https://agentmods.dev/badge/skills/aksoftcode/aicrew/aicrew-terse/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/aksoftcode/aicrew/aicrew-terse"><img src="https://agentmods.dev/badge/skills/aksoftcode/aicrew/aicrew-terse.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 | $0.00024 | $0.00296 |
| Opus 5.5 | $0.00010 | $0.00118 |
| Sonnet 5.5 | $0.00005 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
aicrew-terse 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
Deprecated. Use the
leanskill instead.leanenables terse/caveman output and is the canonical verbosity toggle.aicrew-terseis kept for backward compatibility and will not be updated.
aicrew-terse (Codex) — deprecated, use lean
Codex does not support slash commands. Use this skill when the user asks for "/terse" or wants to re-enable lean output.
Preferred: Use the lean skill going forward. lean covers terse-on behavior. Use aicrew-normal to go verbose.
What it does
Re-activates caveman/lean output mode for the rest of this session:
- Lead with answer or action
- Short sentences, compact fragments OK
- No filler, pleasantries, or hedging
- Verbatim: code blocks, commands, paths, flags, errors, versions
- Context-economy reads: diff/tree/search before file reads
Source of truth
~/Agents/agents/caveman.md~/Agents/agents/terse.md
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 First seen · 30 lines · 24 tokens per session scan A fe6b253b5fcb
aicrew-terse is a skill published in the GitHub repository AKSoftCode/aicrew (3 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 296 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.
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