---
name: tech-radar-boot
description: Use when choosing or evaluating a technology (framework, database, library, cloud tool) — injects Tikal Israeli Tech Radar context (adoption ring, quadrant, opinion, Keep/Start alternatives for Stop items) and pairs the selection with ADR capture via /architect-specify; invoked from team-boot's Class Boots catalog (formerly tech-radar-context).
---

# 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:

- Selecting a framework, library, database, message broker, or cloud tool.
- Comparing options ("X vs Y", "should we use Z").
- Designing a system, service, or pipeline where stack decisions are implied.
- Reviewing an existing stack for modernization or replacement.
- A tech stack choice emerges mid-session (the ADR detection trigger).

Do **not** invoke it for pure business/product questions with no technology
selection, or when the user explicitly says to ignore the radar.

Manual invocation:
```
/tech-radar-boot               # inject radar context for the current prompt
/tech-radar-boot redis vs kafka
```

(`/tech-radar-context` still works as a deprecated alias for this skill.)

## Core Process

### Step 1: Extract Candidate Technologies

From the current prompt (or the description provided by an invoking skill),
extract every named or clearly implied technology: languages, frameworks,
libraries, databases, brokers, CI/CD tools, cloud services, AI/LLM tooling,
build tools, etc. Normalize obvious aliases (e.g. "postgres" → "PostgreSQL",
"k8s" → "Kubernetes", "GH Actions" → "GitHub Actions").

If the prompt implies a category without naming a product (e.g. "we need a
vector database", "pick a Python web framework"), treat the category as a query
and surface the radar's recommended options in that space.

### Step 2: Query the Live Radar Dataset

Execute the deterministic search helper script (relative to this skill directory):

POSIX (bash + jq):
```bash
bash scripts/radar-search.sh <tech1> [tech2 ...]
```

Windows (PowerShell):
```powershell
pwsh scripts/radar-search.ps1 <tech1> [tech2 ...]
```

Or for JSON output (add `--json` for bash, `-Json` for PowerShell).

The script fetches the radar JSON fresh from `https://tikalk.com/radar.json`,
handles alias mapping (`k8s` → `Kubernetes`, `postgres` → `PostgreSQL`, `gh actions` → `GitHub Actions`, etc.), extracts Tikal's `<p>Why?</p>` opinion, and formats the markdown table automatically.

If a technology appears in multiple placements with conflicting rings (e.g.,
`Node.js` is both `DevOps: Stop` and `DevOps: Keep`), the script detects and
flags it with a **Conflicting Guidance** note.

**Schema of the live radar JSON** (`https://tikalk.com/radar.json`):
```json
{
  "title": "Explore the Tech Radar",
  "quadrants": ["DevOps", "Backend", "AI/ML", "Web/Mobile"],
  "rings": ["Try", "Start", "Keep", "Stop"],
  "blips": [
    {
      "name": "FastAPI",
      "quadrant": "Backend",
      "ring": "Keep",
      "description": "<p>Why?</p>\n<p>...Tikal's opinion...</p>\n<p>Description</p>\n<p>...</p>",
      "isNew": false
    }
  ]
}
```

### Step 3: Match Blips

For each candidate from Step 1, find matching blips by `name` (case-insensitive,
alias-aware, allowing minor version suffixes like "Airflow 2" / "Airflow 3" and
partial matches like "Redux" → "Redux Toolkit"). A candidate may match multiple
blips across quadrants — keep them all.

For category queries (Step 1), select the strongest radar recommendations in
that space: prefer `Keep`/`Start` blips in the matching quadrant, and note any
`Stop` blips as things to avoid.

### Step 4: Extract Tikal's Opinion

For every matched blip, parse the `description` HTML:

- The text inside the `<p>Why?</p>` block (up to the next `<p>Description</p>`)
  is **Tikal's opinion / rationale** — the primary signal.
- The `<p>Description</p>` block is neutral background — use only if helpful.

Strip HTML tags to plain text and condense the "Why?" to one or two sentences
for the context table (quote it more fully when the ring is `Stop` or when the
user is directly weighing that technology).

### Step 5: Recommend Alternatives for `Stop`

When a candidate matches a `Stop` blip (or is a legacy technology the radar
clearly discourages), select Tikal-aligned replacements from the **same
quadrant** on `Keep` or `Start`, guided by the "Why?" text. Common examples the
dataset supports:

- Airflow 2 → Airflow 3 / Dagster
- Create React App → Vite / Next.js
- Jenkins → GitHub Actions / GitLab CI / Tekton
- requirements.txt / Poetry → uv
- Moment.js / Luxon → day.js / date-fns
- Redux / Redux Toolkit → Zustand / TanStack Query
- Ant Design / Styled Components → Tailwind CSS / shadcn/ui / Radix UI

Do not hardcode substitutions beyond what the loaded dataset supports — derive
alternatives from the radar's actual `Keep`/`Start` blips in that quadrant.

### Step 6: Inject Tech Radar Context (Output Contract)

Emit a **Tikal Tech Radar Context** section in the visible response, before the
task answer, so downstream reasoning is grounded in the radar:

```markdown
## Tikal Tech Radar Context

| Technology | Quadrant | Ring | Tikal's Opinion (Why?) |
|------------|----------|------|------------------------|
| FastAPI | Backend | Keep | Better alternative to Flask; async, fast, big and growing community. |
| Jenkins | Backend | Stop | Plugin hell + XML config; legacy vs GitHub Actions / GitLab CI / Tekton. |

**Radar guidance**
- ✅ Keep/Start: FastAPI — safe to adopt.
- ⚠️ Stop: Jenkins → consider GitHub Actions, GitLab CI, or Tekton (see Why? above).

_Source: Tikal Israeli Tech Radar (live: https://tikalk.com/radar.json) · N technologies matched._
```

- One row per matched blip (include duplicates across quadrants when relevant).
- Group a short **Radar guidance** list: safe-to-adopt vs avoid-with-alternatives.
- Add a `_Source_` line noting the data came from the **live radar source** and
  how many technologies matched.

If no candidate technology matches any blip, state that plainly with an empty
table and a `_Source_` line (e.g. `_Source: … · 0 technologies matched._`) —
do not fabricate radar placements.

### Step 7: Capture the Selection (Decision Pairing)

A technology selection is an **ADR-class decision**:

| Trigger | Action |
|---------|--------|
| Tech stack chosen ("we'll use X") | ADR → suggest `/architect-specify`, citing the radar rows that informed it |
| "X vs Y" comparison resolved | ADR → suggest `/architect-specify` with the comparison outcome |
| `Stop`-ring technology retained anyway | ADR → suggest `/architect-specify` documenting why the radar guidance was overridden |

Add/refresh rows in the **Session Decision Ledger** (Decision | Type |
Captured? | Skill) for the selection. If `architect-boot` was already
invoked this session, extend its ledger rows with the radar evidence; at
session end, prompt to run `/architect-specify` for any unrecorded tech
selections.

## Failure Handling

- Live fetch fails (network error, timeout, invalid JSON) → the script exits
  non-zero with a clear error message to stderr. The skill must emit an empty
  context table noting the Tech Radar source was unreachable and continue the
  user's task without radar context — never substitute stale cached or
  bundled data as if it were current.
- No matches → empty table + `0 technologies matched` line.

## Red Flags

- Fabricating a ring, quadrant, or "Why?" opinion for a technology that is not
  in the loaded dataset — report `0 matches` instead.
- Silently substituting cached, bundled, or stale radar data when the live
  fetch fails — always report when the radar source is unreachable, never
  present old data as current.
- Hardcoding `Stop`→alternative substitutions not backed by the loaded radar.
- Reporting the neutral `<p>Description</p>` text as Tikal's opinion — the
  opinion lives in the `<p>Why?</p>` block.
- Ignoring duplicate blips: the same technology can sit in different quadrants
  with different rings; surface each relevant placement.
- Treating the skill load as the work — the Core Process must actually run and
  produce the Tech Radar Context table.
- Injecting radar context but skipping the capture pairing — a tech selection
  that informed no ADR is a decision that evaporated.

## Verification

- Candidate technologies were extracted from the prompt (or category queries
  formed when no product was named).
- The radar dataset was fetched live from `https://tikalk.com/radar.json`.
- A **Tikal Tech Radar Context** table was produced with columns Technology /
  Quadrant / Ring / Tikal's Opinion (Why?), with the opinion sourced from the
  `<p>Why?</p>` block.
- `Stop`-ring matches include Tikal-aligned `Keep`/`Start` alternatives from the
  same quadrant, derived from the dataset.
- A `_Source_` line reports the live-radar source and the match count; a no-match
  run yields an empty table plus `0 technologies matched` rather than fabricated
  data. On fetch failure, an error is reported and the skill continues without
  radar context.
- Tech selections made this session appear in the Session Decision Ledger with
  `/architect-specify` as the capture skill.
## Configuration

- Data source: `https://tikalk.com/radar.json` (live-fetched on every invocation;
  no bundled snapshot or cache).
- Fetch timeout: 10 seconds. On fetch failure, the skill continues without radar
  context rather than blocking or substituting stale data.