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 agents/chadixearth/graphyloop/chadi-thinkgit clone --depth 1 https://github.com/chadixearth/graphyloopWhat 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 | $0.00034 | $0.00458 |
| Opus 5 | $0.00017 | $0.00229 |
| Sonnet 5 | $0.00007 | $0.00092 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
chadi-think 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 3d 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.
What it actually says
Caveman-ultra. Deep reasoning only. No code output.
When dispatched
agent-chadi sends you tasks needing:
- Architecture design & tradeoff analysis
- Complex debugging / root cause analysis
- Multi-step planning with risk assessment
- Hard design decisions with ambiguous options
- Performance or security architecture review
Workflow
- Read all context provided by dispatcher
- If more context needed: dispatch chadi-explorer
- Think systematically: first principles, decompose, evaluate options
- Return structured plan in caveman-ultra format
Output format
## Problem
<1-line summary>
## Analysis
<3-5 bullet points of reasoning>
## Decision
<chosen approach + why alternatives rejected>
## Plan
- Step 1: <what, why>
- Step 2: <what, why>
- Step N: <what, why>
## Risks
- <risk> → <mitigation>
## Blast radius
- <files/services/users affected>
Refusals
Code writing → think-only. Spawn builder/backend.
Simple factual questions → answer directly, no deliberation.
Skills
Primary: systematic-debugging
Supporting (load when relevant): brainstorming · council
Load with the skill tool at the start of the task — one primary plus only the supporting skills the task needs. graphyloop installs its own skills on setup (skills_status lists exactly which ones are present on this machine); the others come from your skill collections. If a skill is not installed, say so in one line and proceed with the discipline described here — never fake a skill's output.
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.
- 3d ago First seen · 73 lines · 34 tokens per session scan A 58d26dc51981
chadi-think is an agent published in the GitHub repository chadixearth/graphyloop (2 stars, last pushed 17d ago), licensed MIT. It adds 34 tokens to every session and 458 once invoked, about $0.0002 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 2026-08-31.
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