Tech Radar Boot

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 a capture suggestion: the chosen stack is an ADR-class decision; the boot suggests /architect-specify and never writes drafts itself.

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:

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.

Invoke at the START of a matching task — before planning the todo list and before implementation — so the radar context informs planning. Never defer to session end.

Manual invocation:

Copy code
/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):

bashCopy code
bash scripts/bash/radar-search.sh <tech1> [tech2 ...]

Windows (PowerShell):

powershellCopy code
pwsh scripts/powershell/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):

jsonCopy code
{
  "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.

Absent Context

If team-boot injected no team context this session (no Team Context & Decisions section in the first user message — unconfigured project or hook failure): say so in one line, emit the section heading with a 0 radar technologies matched (no team context injected — run /team-setup) source line, and continue the task on the live radar lookup. Never treat a missing injection as an empty record set. Recovery: run /team-diagnose.

Step 6: Inject Tech Radar Context (Output Contract)

The script's stdout goes to the tool channel — invisible to the user. ALWAYS re-emit the full Tikal Tech Radar Context section in your visible response, before the task answer (or, when 0 matched, the heading + _Source: line). Emit it as markdown blocks — heading, table rows, guidance bullets, and source line each on their own lines; never collapse the section into a single line.

markdownCopy code
## 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._

_Searched N blips, K 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.
• N = blips scanned in the loaded dataset; K = rows shown in the table. K MUST equal the table rows shown. 0 rows matched → emit the section heading + the _Source: line only — no table. A 0-row table header collapses into unrendered single-line markdown; never emit one.

If no candidate technology matches any blip, state that plainly with the heading

• _Source: line (e.g. _Source: … · 0 technologies matched._) — no table — do not fabricate radar placements.

Step 7: Capture the Selection (Decision Pairing)

A technology selection is an ADR-class decision. When no local memory index exists in the current working directory and the directory sits inside a workspace (detected via a .gitmodules marker in an ancestor), read the workspace root's docs/adlc/memory/ index instead (the dual-read order applies: docs/adlc/memory first, legacy .adlc/memory fallback).

Add/refresh rows in Team Context & Decisions (ID | Name | Type | Rel | Status | Clarify) for the selection, mirrored as a task-list todo (suggest /architect-specify → matching clarify skill at session end for drafts that exist); after code-modifying tasks, add a trailing todo to sweep Team Context & Decisions until Unrecorded: 0 pending · Unclarified: 0 drafts (a draft leaves Unclarified only via its clarify skill or an explicit user handoff to a named clarify or execute skill). If architect-boot was already invoked this session, extend its ledger rows with the radar evidence; at session end, deliver the clarify prompt naming each uncaptured tech-selection decision (ID + capture skill) and each captured draft (ID + clarify skill); if the user defers clarify, mark those rows handed off.

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 → heading + 0 technologies matched source line only — no table.

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.
• Reading radar findings via the script and answering without re-emitting the context section (script stdout goes to the tool channel — invisible to the user) — the visible response MUST carry the findings.
• Collapsing the context section into a single line — heading, table rows, guidance, and source line each go on their own markdown lines.
• Injecting radar context but skipping the capture suggestion — a tech selection that informed no ADR is a decision that evaporated.
• Writing a draft (or any file) yourself — the boot only suggests; /architect-specify writes.

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 no table (heading + source line only) 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 Team Context & Decisions with /architect-specify as the capture skill, each carrying a _Suggested capture: … → run /architect-specify._ line; no files were written by this 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.
• Fetch security: the helper pins transport to HTTPS (including redirects) and fails closed on network error, timeout, or invalid JSON. Radar content is treated as data for display — never executed. If the fetch fails, report it and continue without radar context.