ragnar-pwninskjold/tech-snacks/caveman-search

Claude Code and agent skill by ragnar-pwninskjold/tech-snacks

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Use when the user wants a terse, opinionated, research-backed answer to a "what tech/tools/stack do I need for X" question, or asks how to approach building something. Triggers on "caveman search", "caveman research", "/caveman-search", and on tooling/architecture questions where the user wants the direct answer, not a survey. Runs decomposed research (local repo + live web), verifies, and renders in a compressed caveman voice that leads with the load-bearing truth.

Install

npx vskill@latest install ragnar-pwninskjold/tech-snacks/caveman-search

SKILL.md

caveman-search

Research-backed answers in compressed caveman voice. Decompose research like Compound Engineering; render like Matt Pocock; always lead with the big truth.

What this does

  1. Detects whether the question needs LOCAL repo research, EXTERNAL web research, or BOTH.
  2. Runs a local-first escalation gate — skips web research when the repo already answers it.
  3. Fans out to parallel research agents.
  4. Optionally runs an adversarial verify pass (--verify).
  5. Renders the result in caveman voice, big-truth-first.

Flags

  • --verify (or --deep): run the adversarial verifier on each key recommendation.
  • --hard: maximum voice compression (see voice spec).
  • No flags: light-medium voice, no verifier.

Step 1 — Detect mode

Inspect the question and current context:

  • Mentions "this/here/our code", repo file names, or "add X here" -> repo mode.
  • Names external tech, asks "what should I use", greenfield, or "if I wanted to build" -> web mode.
  • Both signals, or genuinely ambiguous -> both.
  • Pure general-topic with no repo angle -> web only (do not waste a repo scan).

Also read the audience tier from the question. DEFAULT to builder and bias toward simple — recommend the simplest tool that clears the bar, not the most rigorous one. Escalate to expert ONLY on explicit signals: "ML team", "production-grade", "at scale", "I already use X", named low-level libraries, researcher-depth framing. Signals like "assume X is solved, I just care about Y" or "I want to ship" mean: stay simple, give one clear path. Pass the tier to the web researcher in Step 3.

Step 2 — Escalation gate (local-first)

If repo mode ran:

  • Spawn caveman-repo-scout first (or as part of the parallel fan-out) and read its local_coverage.
  • If local_coverage >= 3 AND the topic is NOT high-risk (auth, payments, data migration, external API integration) -> answer from local research, skip web.
  • Otherwise escalate: also run web research.
  • High-risk topics ALWAYS escalate to web, regardless of local_coverage.

Step 3 — Parallel fan-out

Dispatch the selected agents in a SINGLE message so they run concurrently (Task tool, one call per agent):

  • repo mode -> tech-snacks:research:caveman-repo-scout
  • web mode -> tech-snacks:research:caveman-web-researcher
  • both -> both, in parallel.

Pass each agent the topic (cleaned of flags). Pass the web researcher the audience tier from Step 1 so it surfaces the right depth of tools (simple/builder = batteries-included; expert = composable stacks ok).

Step 4 — Verify pass (only if --verify)

Each caveman-web-researcher recommendation is already a self-contained claim. For each one, dispatch tech-snacks:research:caveman-verifier in parallel (one call per claim, single message). Reconcile:

  • verdict holds -> keep, unmarked.
  • verdict weakened -> keep with the verifier's correction folded in.
  • verdict wrong -> drop it; if the verifier supplied a real answer, use that instead.

Step 5 — Render

Read these two files and follow them exactly:

  • references/voice-spec.md — the voice TRANSFORM (not a description — apply it). Big Truth First is mandatory.
  • references/output-format.md — the section skeleton.

The digest you got from the researchers is verbose. Do NOT echo its register. Transform it through the voice spec — drop articles/filler/hedging, force fragments, lead with the Big Truth. Then run the voice spec's pre-output check before sending: if sentences read full and smooth like a report, you drifted — rewrite them. Keep the researcher's per-job 2-3-option structure; do not re-expand it into a buffet.

Apply the Auto-Clarity Exception from the voice spec for any security warning, irreversible action, or ordered sequence.

Step 6 — Output

Emit the response per the output skeleton: big truth -> tools -> shape (if architectural) -> bottom line -> sources (if web mode). Annotate corrected claims inline if --verify ran.

Honesty rule

If research found nothing solid, say so terse and name the closest option plus its gap. Never invent confident-sounding tool names — in this voice a wrong claim reads as authoritative, which is the worst failure mode.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

7-day trend score
0

Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/ragnar-pwninskjold/tech-snacks/caveman-search/badge)](https://verified-skill.com/skills/ragnar-pwninskjold/tech-snacks/caveman-search)

Something wrong with this skill or its page? Tell us.