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-quickgit 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-quick)<a href="https://agentmods.dev/skills/aksoftcode/aicrew/aicrew-quick"><img src="https://agentmods.dev/badge/skills/aksoftcode/aicrew/aicrew-quick/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-quick"><img src="https://agentmods.dev/badge/skills/aksoftcode/aicrew/aicrew-quick.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 | $0.00027 | $0.00752 |
| Opus 5.5 | $0.00011 | $0.00301 |
| Sonnet 5.5 | $0.00005 | $0.00150 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
aicrew-quick 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.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aicrew /quick (Codex)
Use for scoped tasks that don't need the full /dev ceremony.
Scout the relevant code first, then act with surgical, goal-driven changes.
Token foundation (mandatory)
/dev, /fix, and /quick all share the same 11-capability token-saving stack — only pipeline depth differs. Full reference: ~/Agents/docs/token-foundation.md. Stack: graph-first (codebase-memory-mcp), speculative Scout → verify (SCOUT schema, two-model routing), Karpathy guardrails, layered guardrails (guardrails-taxonomy.md), context-economy read policy, security-guard.py hooks, .ai/state checkpoints, /compact between phases, /handoff on tool switch, optional context-mode + token-optimizer-mcp, caveman default output. For /quick, Scout IS Phase 1 (built-in, always first); Act is Phase 2.
Default output
Caveman/lean style by default. See ~/Agents/agents/caveman.md and ~/Agents/agents/context-economy.md.
/normal or /lean off restores verbose.
Source of truth
~/Agents/commands/quick.md~/Agents/agents/karpathy-guardrails.md- Project overrides in
.ai/skills/and repoAGENTS.md(if present)
Token foundation (mandatory — both phases)
- Graph-first: codebase-memory-mcp (search_graph → trace_path → get_code_snippet) before any Grep/Read
- Speculative context: Scout IS Phase 1 (cheap model); emit SCOUT: schema; verify before Act
- Layered guardrails: security-guard.py (input) → scope lock (SCOUT Goal:) → karpathy-guardrails (Act) → context budget
- Context economy: always on; state saved at Checkpoint B
- Two-model routing: Scout on haiku/mini; Act on sonnet/opus
- See: ~/Agents/docs/token-foundation.md
Workflow summary
- Scout — graph-first discovery before touching anything:
- Graph MCP (codebase-memory-mcp):
list_projects→search_graph→trace_path→get_code_snippet - Fallback:
git diff --name-only, targeted grep, slice-reads - Emit and verify SCOUT: schema (Goal / Status / Constraints verbatim / Files / Call chain / Next action / Tests / Risks)
- Graph MCP (codebase-memory-mcp):
- Act — implement with Karpathy guardrails:
- Think Before Coding: Scout verified before any edit
- Simplicity First: fewest files, smallest change
- Surgical Changes: diff-sized edits only, no unrelated reformats
- Goal-Driven Execution: every edit traces to the Goal line; stop when done
- Write/update
.ai/state/AI_STATE.<tool>.<session>.mdat Checkpoint B and after Act
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 · 55 lines · 27 tokens per session scan A 6571f4748d8d
aicrew-quick is a skill published in the GitHub repository AKSoftCode/aicrew (3 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 752 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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