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 ragnar-pwninskjold/tech-snacks --skill caveman-searchgit clone --depth 1 https://github.com/ragnar-pwninskjold/tech-snacksWrote 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/ragnar-pwninskjold/tech-snacks/caveman-search)<a href="https://agentmods.dev/skills/ragnar-pwninskjold/tech-snacks/caveman-search"><img src="https://agentmods.dev/badge/skills/ragnar-pwninskjold/tech-snacks/caveman-search/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/ragnar-pwninskjold/tech-snacks/caveman-search"><img src="https://agentmods.dev/badge/skills/ragnar-pwninskjold/tech-snacks/caveman-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00111 | $0.01117 |
| Opus 5 | $0.00056 | $0.00558 |
| Sonnet 5 | $0.00022 | $0.00223 |
| Haiku 4.5 | $0.00011 | $0.00112 |
Grade A, and why
caveman-search 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 12d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Detects whether the question needs LOCAL repo research, EXTERNAL web research, or BOTH.
- Runs a local-first escalation gate — skips web research when the repo already answers it.
- Fans out to parallel research agents.
- Optionally runs an adversarial verify pass (
--verify). - 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-scoutfirst (or as part of the parallel fan-out) and read itslocal_coverage. - If
local_coverage >= 3AND 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.
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.
- 12d ago First seen · 75 lines · 111 tokens per session scan A 3e695e700b99
caveman-search is a skill published in the GitHub repository ragnar-pwninskjold/tech-snacks (132 stars, last pushed 24d ago), licensed MIT. It adds 111 tokens to every session and 1,117 once invoked, about $0.0006 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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