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 kunalsuri/ai-fication-kit --skill verify-ai-readinessgit clone --depth 1 https://github.com/kunalsuri/ai-fication-kitWrote 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/kunalsuri/ai-fication-kit/verify-ai-readiness)<a href="https://agentmods.dev/skills/kunalsuri/ai-fication-kit/verify-ai-readiness"><img src="https://agentmods.dev/badge/skills/kunalsuri/ai-fication-kit/verify-ai-readiness/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/kunalsuri/ai-fication-kit/verify-ai-readiness"><img src="https://agentmods.dev/badge/skills/kunalsuri/ai-fication-kit/verify-ai-readiness.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 | $0.00336 |
| Opus 5 | $0.00014 | $0.00168 |
| Sonnet 5 | $0.00005 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
verify-ai-readiness 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
Assess how ready this repository is for agentic work. Read-only; output one report.
The maturity scale
- Level 0 — Opaque. No agent entry files; agents crawl and guess.
- Level 1 — Scaffolded. Kit installed; maps exist but are placeholders.
- Level 2 — Drafted. /cold-start ran; maps populated but
[inferred]. - Level 3 — Verified. Human audit done: Stability set, core rows
[verified]. The minimum bar for letting an agent build features. - Level 4 — Maintained. Feature catalog exists; knowledge updated on merge; audits recur; evaluations recorded in ai/lab/.
Method
Score each: entry files (CLAUDE.md/AGENTS.md), MODULE_MAP coverage & verification
ratio (% rows [verified]), FEATURE_MAP/CATALOG coverage, conventions, diagrams,
ai/lab/ activity. Evidence = file contents only; no speculation.
Output
Write ai/analysis/audit-reports/<YYYY-MM-DD>-readiness.md: overall level, per-area
table (area · evidence · level), the SINGLE most valuable next action, and any
agent-blocking gaps (anything that would make a feature build unsafe today).
Tag the report [inferred].
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 · 29 lines · 27 tokens per session scan A 34f5ee7c26b4
verify-ai-readiness is a skill published in the GitHub repository kunalsuri/ai-fication-kit (3 stars, last pushed 9d ago), licensed Apache-2.0. It adds 27 tokens to every session and 336 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 2026-08-31.
Other skills, from other repositories
close-my-loops
Build and maintain a personal work profile and open-loop tracker for the user's own job — a markdown file covering their org, key contacts, communication style, active initiatives, and open loops synthesized from their own email/Slack; a Cowork Project setup so that file is actually read every session; a scheduled…
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
anti-sleep
Keep a Mac awake with caffeinate during long builds, downloads, or supervised automation runs.
accint-commitments
Triage acc's open promises and close them with honest real-world verdicts via accact(runtime="outcome").
gsd-surface
Toggle which skills are surfaced — apply a profile, list, or disable a cluster without reinstall.
gsd-capture
Capture ideas, tasks, notes, and seeds to their destination.