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 tikalk/adlc-team-skills --skill tech-radar-bootgit clone --depth 1 https://github.com/tikalk/adlc-team-skillsWrote 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/tech-radar-boot)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/tech-radar-boot"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/tech-radar-boot/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/tech-radar-boot"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/tech-radar-boot.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 | $0.00078 | $0.03249 |
| Opus 5.5 | $0.00031 | $0.01300 |
| Sonnet 5.5 | $0.00016 | $0.00650 |
| Haiku 4.5 | $0.00008 | $0.00325 |
Grade A, and why
tech-radar-boot 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 10d 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tech-radar-boot
Overview
One of the five class boots surfaced by team-boot's Class Boots
catalog, this skill handles technology selection. It surfaces
Tikal's opinion on the technologies relevant to the current prompt so a
tech stack choice is informed by the Israeli Tech Radar, and it pairs the
selection with decision capture: the chosen stack is an ADR-class decision
that should be recorded via /architect-specify.
The radar lookup works like team-discover, but its search surface is the
Tikal Tech Radar dataset (fetched live from https://tikalk.com/radar.json)
instead of the team CDR index: it extracts candidate technologies from the
prompt, matches them against radar blips, and injects a compact
Tech Radar Context table (ring, quadrant, Tikal's "Why?" opinion) plus
Tikal-aligned alternatives for anything on Stop.
The radar has four quadrants — DevOps, Backend, AI/ML,
Web/Mobile — and four adoption rings:
| Ring | Meaning | Guidance |
|---|---|---|
Try |
New stuff that on the surface seems good (good press, new solution) | Explore / evaluate; not yet endorsed for production use |
Start |
A good solution more companies should use; if in beta, active progress and contribution | Recommend adopting on new projects |
Keep |
Stable release (non-beta) with major supporter acceptance (large community, used by corporates) | Recommend by default for current & new work |
Stop |
Items we recommend companies stop using — better alternatives exist | Warn against; recommend a Keep/Start alternative |
Each blip's description embeds an HTML <p>Why?</p> block followed by a
<p>Description</p> block. The Why? text carries Tikal's explicit stance
and rationale — that is the opinion to surface. A technology may appear more
than once (different quadrants) with different rings; report each relevant
placement.
When to Use
Model-invoke this skill whenever the prompt involves choosing or evaluating technology, for example:
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.
- 10d ago Changed · +4 lines b20027a65fbf
- 13d ago Changed · +17 lines 860fc587f887
- 15d ago Changed · +1 lines 01f69e1a504b
- 16d ago Changed · +7 lines 0835de9c775c
- 25d ago First seen · 251 lines · 78 tokens per session scan A 1e59edcb0d56
tech-radar-boot is a skill published in the GitHub repository tikalk/adlc-team-skills (141 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 3,249 once invoked, about $0.0003 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 2026-09-21.
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