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 akasecurity/ai-tc --skill setupgit clone --depth 1 https://github.com/akasecurity/ai-tcWrote 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/akasecurity/ai-tc/setup)<a href="https://agentmods.dev/skills/akasecurity/ai-tc/setup"><img src="https://agentmods.dev/badge/skills/akasecurity/ai-tc/setup/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/akasecurity/ai-tc/setup"><img src="https://agentmods.dev/badge/skills/akasecurity/ai-tc/setup.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 | $0.00023 | $0.13857 |
| Opus 5.5 | $0.00009 | $0.05543 |
| Sonnet 5.5 | $0.00005 | $0.02771 |
| Haiku 4.5 | $0.00002 | $0.01386 |
Grade B, and why
aka-setup scanned grade B with 3 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 6d 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.
Downloads and executes remote codemediumSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://raw.githubusercontent.com/akasecurity/ai-tc/bin-latest/tools/installer/install.sh | sh Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Reads agent configuration directorieslowAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
(`~/.gemini/config/plugins/aka-antigravity`). If the plugin was Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://raw.githubusercontent.com/akasecurity/ai-tc/bin-latest/tools/installer/install.sh | sh How it starts
The opening of the file, as written. The whole thing — 1,052 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AKA setup wizard
You are onboarding the AKA Security plugin for this machine. AKA works
fully locally with zero backend and zero Docker: detection runs in-process
and findings persist to a local SQLite store at ~/.aka/data/aka.db.
This wizard tells a calibration story: introduce AKA → show what it does → offer one retroactive scan → report the real numbers it found and the posture it recommends → apply on confirmation → show the installed summary → hand off to the dashboard. Everything the user sees is derived from their actual history — never a fabricated or demo number. When there isn't enough history to judge, the wizard falls back to a conservative severity-derived floor instead of guessing.
The false-positive/severity judgment needs the raw (unmasked) findings to rate
them accurately, so it sends them to the model API through separate agy
subprocesses (a large history is judged in several batches). Two things
cross for each finding: its raw value, and about 120 characters of the
surrounding transcript text on either side of it — re-masked first, so any
other detectable secret in that window never leaves raw. The transcript
file's path, the value's fingerprint, and the fingerprint key version are
dropped before egress. A copy of the raw value leaves the machine, sent
to the model provider like any other Antigravity prompt. You act only on the
raw-free plan the subprocesses print back.
Two limits of this host are worth knowing before you consent, because they are weaker than the Claude Code and Codex plugins' equivalents:
- The
agyCLI documents no ephemeral mode. Every run is written to your conversation store under~/.gemini/antigravity/brain/, raw values and all — the same store this backfill scans. AKA therefore deletes the judge's own conversation itself as soon as the run ends. That deletion is best effort: if the process is killed between the write and the cleanup, the conversation stays on disk until you remove it. - Deleting the conversation is not network isolation. It is a local-write cleanup only; it cannot recall what was already sent.
Reading history is granted in step 1; sending findings to the model is a distinct consent, collected in step 3 before the judgment pipe runs — the judge refuses to run without it.
Follow the steps below in order. Nothing is written to the policy store until step 5 (or a floor fallback in step 3 if the calibration can't complete).
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.
- 6d ago Changed · +1 lines e864c4366c44
- 13d ago Changed · +67 lines afa7f1cbeb35
- 1mo ago Changed · +27 lines 47daeaeb9492
- 1mo ago Changed · +10 lines a7bea595b9b1
- 1mo ago First seen · 947 lines · 23 tokens per session scan B e0350fda5508
aka-setup is a skill published in the GitHub repository akasecurity/ai-tc (13 stars, last pushed today), licensed Apache-2.0. It adds 23 tokens to every session and 13,857 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 3 findings (downloads and executes remote code, reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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