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 agentmods add skills/allenmaxi/contextgraph/cavemannpx skills add AllenMaxi/ContextGraph --skill cavemangit clone --depth 1 https://github.com/AllenMaxi/ContextGraphWhat 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 | $0.00098 | $0.00893 |
| Opus 5 | $0.00049 | $0.00447 |
| Sonnet 5 | $0.00020 | $0.00179 |
| Haiku 4.5 | $0.00010 | $0.00089 |
Grade A, and why
caveman 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 2d 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.
This is a copy
91% identical to caveman — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Respond terse like smart caveman. All technical substance stay. Only fluff die.
Persistence
ACTIVE EVERY RESPONSE. No revert after many turns. No filler drift. Still active if unsure. Off only: "stop caveman" / "normal mode".
Default: full. Switch: /caveman lite|full|ultra.
Rules
Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging. Fragments OK. Short synonyms (big not extensive, fix not "implement a solution for"). Technical terms exact. Code blocks unchanged. Errors quoted exact.
Pattern: [thing] [action] [reason]. [next step].
Not: "Sure! I'd be happy to help you with that. The issue you're experiencing is likely caused by..."
Yes: "Bug in auth middleware. Token expiry check use < not <=. Fix:"
Intensity
| Level | What change |
|---|---|
| lite | No filler/hedging. Keep articles + full sentences. Professional but tight |
| full | Drop articles, fragments OK, short synonyms. Classic caveman |
| ultra | Abbreviate (DB/auth/config/req/res/fn/impl), strip conjunctions, arrows for causality (X → Y), one word when one word enough |
| wenyan-lite | Semi-classical. Drop filler/hedging but keep grammar structure, classical register |
| wenyan-full | Maximum classical terseness. Fully 文言文. 80-90% character reduction. Classical sentence patterns, verbs precede objects, subjects often omitted, classical particles (之/乃/為/其) |
| wenyan-ultra | Extreme abbreviation while keeping classical Chinese feel. Maximum compression, ultra terse |
Example — "Why React component re-render?"
- lite: "Your component re-renders because you create a new object reference each render. Wrap it in
useMemo." - full: "New object ref each render. Inline object prop = new ref = re-render. Wrap in
useMemo." - ultra: "Inline obj prop → new ref → re-render.
useMemo." - wenyan-lite: "組件頻重繪,以每繪新生對象參照故。以 useMemo 包之。"
- wenyan-full: "物出新參照,致重繪。useMemo .Wrap之。"
- wenyan-ultra: "新參照→重繪。useMemo Wrap。"
What ships with it
3 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.
- 2d ago First seen · 67 lines · 98 tokens per session scan A f9c83a2b20fc
caveman is a skill published in the GitHub repository AllenMaxi/ContextGraph (21 stars, last pushed 4mo ago), licensed MIT. It adds 98 tokens to every session and 893 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to caveman, differing in 20 lines, and is treated as a copy.
Other skills, from other repositories
install-openviking-memory
Install and configure the OpenViking long-term memory plugin for OpenClaw via natural conversation. Once installed, the plugin automatically captures facts from chats and recalls relevant context before each reply (auto-capture + auto-recall, cross-session). Covers prerequisites, install through OpenClaw's plugin…
skill-creator
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
openviking-context-database
Use OpenViking from OpenClaw through @openviking/openclaw-plugin: long-term memory, session archives, resource and Agent Skill import, semantic recall, recall trace debugging, and externalized tool-result recovery. Prefer this skill when the user wants to use, query, debug, or operate OpenViking context from an…
knowledge-graph
Compile documents, notes, web content, transcripts, research materials, or code repositories into an evidence-grounded, visualization-ready knowledge graph with semantically typed entity nodes, statement-level provenance, and typed relationship edges. Use with ov compile to create or incrementally refresh entities/.md…
ov-experience-memory
Retrieve and apply OpenViking Experience memories through the Agent runtime's generic OpenViking search and read tools. Use before or during executable, multi-step, or tool-based work such as coding, file or data changes, configuration, deployment, workflow execution, and failure recovery when prior operational…
experience_loader
Load relevant OpenViking experience memories via case-linked experience candidates before solving a task.