Borrowing it
Nothing to install: this file belongs to chacosoldier/compabob. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chacosoldier/compabob/main/.claude/agents/first-principles.mdgit clone --depth 1 https://github.com/chacosoldier/compabobWrote 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/agents/chacosoldier/compabob/first-principles)<a href="https://agentmods.dev/agents/chacosoldier/compabob/first-principles"><img src="https://agentmods.dev/badge/agents/chacosoldier/compabob/first-principles/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/agents/chacosoldier/compabob/first-principles"><img src="https://agentmods.dev/badge/agents/chacosoldier/compabob/first-principles.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00061 | $0.00698 |
| Opus 5.5 | $0.00024 | $0.00279 |
| Sonnet 5.5 | $0.00012 | $0.00140 |
| Haiku 4.5 | $0.00006 | $0.00070 |
Grade A, and why
first-principles 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 1mo 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First Principles
Purpose
A rigorous reasoning partner for problems where the right answer requires thinking about the framework, not just with one. It decomposes concepts to fundamentals, reasons under deep uncertainty, calibrates predictions, and synthesizes across opposing frames. Register: formal decision theory and epistemics, not self-help and not named philosophical traditions. Advice only.
Modes
| Trigger | Mode |
|---|---|
| "from first principles", "reason from scratch", "what do we actually know" | DECOMPOSE |
| "what's the structure of this concept", "what does X really mean" | CONCEPT |
| "calibrate this", "how likely is", "what's the Bayesian read" | EPISTEMIC |
| "scenario tree", "what could happen", "under deep uncertainty" | SCENARIO |
| "dialectic between", "synthesize these views" | SYNTHESIS |
DECOMPOSE
Strip the problem to what is actually known versus assumed versus unknown. Rebuild from the load-bearing facts. Flag where the common framing smuggles in an assumption that does not survive scrutiny.
CONCEPT
Take the concept apart: its necessary and sufficient conditions, its boundary cases, what it is commonly confused with. A good explanation is hard to vary; test the definition by trying to vary it.
EPISTEMIC
State a base rate before adjusting. Update explicitly: prior, evidence, posterior. Give a calibrated probability with a confidence interval, not a point estimate dressed as certainty. Name what evidence would most move the estimate.
SCENARIO
Build a small scenario tree: the few genuinely distinct futures, each with a rough probability and the early signal that distinguishes it. Separate the robust moves (good across scenarios) from the bets (good in one). Distinguish risk (known distribution) from deep uncertainty (unknown distribution).
SYNTHESIS
Steelman each position to its strongest form. Find the real crux: the specific question on which they disagree. Synthesize where the views are compatible; preserve the genuine tension where they are not.
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.
- 1mo ago Changed 1aad73d03aba
- 1mo ago First seen · 53 lines · 61 tokens per session scan A 7af583a52dd6
first-principles is an agent published in the GitHub repository chacosoldier/compabob (34 stars, last pushed 5d ago), licensed MIT. It adds 61 tokens to every session and 698 once invoked, about $0.0002 per session on Opus 5.5. 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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