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 DDS-Solutions/AI-TadPole-OS --skill aletheia-reasoninggit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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 | $0.00019 | $0.01231 |
| Opus 5 | $0.00010 | $0.00616 |
| Sonnet 5 | $0.00004 | $0.00246 |
| Haiku 4.5 | $0.00002 | $0.00123 |
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 11d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This rewrite transforms the Aletheia Reasoning Protocol from a theoretical description into an operational mandate.
I have introduced Operational Markers (tags), a Verification Rubric, and a Hard-Reset Trigger. This ensures that when the AI invokes this skill, it doesn't just "think" about the problem—it provides a transparent, auditable trail of its reasoning process.
Revised SKILL.md
--- File: SKILL.md
name: aletheia-reasoning description: Structured iterative reasoning framework for deep problem solving, featuring explicit verification loops and refinement stages. when_to_use: "Use for complex math, system architecture, root-cause analysis, and high-risk code refactoring where the cost of failure is high." allowed-tools: Read, Write, Edit, Execute version: 2.0 priority: CRITICAL
🧠 Aletheia Reasoning Protocol
Aletheia is a high-fidelity reasoning framework designed to bridge the gap between simple prediction and rigorous proof. It forces the AI to act as its own adversary to ensure logical consistency and peak accuracy.
⚙️ 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 the generation phase.
2. 🛡️ Verifier [VERIFIER]
The internal adversary. The Verifier must assume the solution is wrong until proven otherwise.
- The Rubric: Every candidate solution must be audited against:
- Logical Continuity: Does step $N+1$ follow logically from step $N$?
- Constraint Adherence: Does this violate any project boundaries or
clean-codestandards? - Edge Case Stress-Test: What happens with null, extreme, or malformed inputs?
- Parity Check: Does this change break existing functionality? The Verifier MUST call the
Executetool to runparity_guard.py(or the equivalent test suite) before assigning a 🟢 Correct verdict.
- Outcomes:
- 🔴 Critically Flawed: Core logic is broken $\rightarrow$ Trigger Hard Reset (Back to Generator).
- 🟡 Minor Fixes: Logic is sound, but contains syntax or minor errors $\rightarrow$ Forward to Reviser.
- 🟢 Correct: Solution is hardened $\rightarrow$ Proceed to Final Output.
What ships with it
1 file 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.
- 11d 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 yesterday), licensed MIT. It adds 19 tokens to every session and 1,231 once invoked, about $0.0001 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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