Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/tikalk/adlc-team-skillsnpx agentmods add skills/tikalk/adlc-team-skills/team-setupWrote 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/tikalk/adlc-team-skills/team-setup)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/team-setup"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/team-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/tikalk/adlc-team-skills/team-setup"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/team-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 439 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00071 | $0.05538 |
| Opus 5 | $0.00036 | $0.02769 |
| Sonnet 5 | $0.00014 | $0.01108 |
| Haiku 4.5 | $0.00007 | $0.00554 |
Grade A, and why
team-setup 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 9d 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 — 504 lines — stays where its author put it; the contents beside it link to each section on GitHub.
team-setup
Overview
team-setup is an interactive skill that guides you through setting up the team AI directives. It presents four modes, explains each option, confirms your choice, and executes the setup.
It is invoked in two ways:
- User-invoked (
/team-setup) — anytime, to configure or check a project. - Model-invoked by
team-boot— automatically at session start when a project has no.adlc/init-options.jsonconfiguration (self-install), so an unconfigured project wires itself without the user knowing the command.
The skill is non-destructive: it never overwrites existing files or directories. If the target path already contains a configured team AI directives, it detects this and offers the "Already configured" mode instead.
When to Use
- Starting a new team from scratch and need a neutral team AI directives scaffold to fill in later.
- Your team already has a directives repo on GitHub and you want to clone it locally.
- You have a local team AI directives directory already (e.g., from a previous project) and want to wire it up.
- You're unsure whether the team AI directives is already configured and want a quick check.
- When the project isn't yet wired to a team AI directives (no
.adlc/init-options.jsonteam_ai_directivesfield). - Automatically via
team-bootwhen it detects an unconfigured project at session start (self-install).
Decline Handling (when model-invoked by team-boot)
When team-boot invokes this skill because the project is unconfigured, the
user may choose not to set up team AI directives right now. Handle decline
explicitly to avoid a re-prompt loop:
- If the user declines at mode selection, do not run any mode. Exit
cleanly and tell
team-bootthe user declined. - Offer a persistent opt-out: "Don't ask again for this project?" On yes
(build mode only), write
.adlc/init-options.jsonwithteam_ai_directives: null:
This marker makesecho '{"team_ai_directives": null}' > ".adlc/init-options.json"team-bootskip setup silently on every future prompt. - In plan/read-only mode, a persistent opt-out cannot be written — the
decline is session-scoped only; tell
team-bootto defer. - Never force a mode; the setup is user-consented at every step.
What ships with it
2 files 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.
- 9d ago First seen · 504 lines · 71 tokens per session scan A 7916d961bb4a
team-setup is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 5,538 once invoked, about $0.0004 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.
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