Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSnpx agentmods add skills/dds-solutions/ai-tadpole-os/aletheia-reasoningWrote 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/dds-solutions/ai-tadpole-os/aletheia-reasoning)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/aletheia-reasoning"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/aletheia-reasoning/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/dds-solutions/ai-tadpole-os/aletheia-reasoning"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/aletheia-reasoning.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 | $0.00029 | $0.01275 |
| Opus 5.5 | $0.00012 | $0.00510 |
| Sonnet 5.5 | $0.00006 | $0.00255 |
| Haiku 4.5 | $0.00003 | $0.00128 |
Grade A, and why
aletheia-reasoning 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / aletheia-reasoning
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Reasoning drift, unverified assumptions, or premature solution emission.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
🧠 Aletheia Reasoning Protocol
Purpose: High-fidelity reasoning framework designed to bridge the gap between simple prediction and rigorous proof by forcing the agent to act as its own adversary. Workflow Binding: Used during
/debug,/refactor, and/audit.
🎯 Progressive Disclosure & L3 Reference Index
Read REQUIRED core workflow below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide / Tool | Purpose | Trigger / When to Load |
|---|---|---|
references/nexus_v3_tadpole_engineer.md |
Sovereign Nexus Engineer v3.0 operational persona & distributed-systems rigor | High-risk architectural refactoring or security reviews |
scripts/aletheia_linter.py |
Deterministic validator for Aletheia reasoning traces ([GENERATOR], [VERIFIER], [FINAL]) |
Verifying compliance of complex reasoning logs or --test validation |
⚙️ The Operational Loop
The agent MUST execute these stages sequentially. Do not skip to Final Output without a Verifier's seal of approval.
graph LR
P[Problem] --> G[Generator]
G --> CS[Candidate Solution]
CS --> V{Verifier}
V -- "Critically Flawed" --> G
V -- "Minor Fixes" --> R[Reviser]
V -- "Correct" --> FO[Final Output]
R --> CS
1. 🏗️ Generator [GENERATOR]
The engine of exploration:
- Goal: Produce a high-probability Candidate Solution.
- Focus: Breadth, creative approach selection, and initial drafting.
- Requirement: Must explicitly state the assumptions made during generation.
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 Changed · -9 lines · +10 tokens per session dd6a6dfd1a9c
- 2mo ago First seen · 114 lines · 19 tokens per session scan A a0dbc94d4fc6
aletheia-reasoning is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,275 once invoked, about $0.0001 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 2026-08-31.
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