README: dataset card with the 2026-10-08 audit

The .history reproduces from .memory with the canon's skill_history.py; every iteration ran under an archived skill whose sha256 matches; both operator seeds account for before/after exactly; publication.json recomputes.

Professor Codephreak · https://github.com/Professor-Codephreak

README.md

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+---
+license: mit
+language:
+  - en
+pretty_name: Jaimla's improvement loop (.memory, .history, SKILL.md)
+size_categories:
+  - n<1K
+task_categories:
+  - text-generation
+tags:
+  - jaimla
+  - sagi
+  - agent-memory
+  - self-improvement
+  - verified-inference
+  - provenance
+  - jsonl
+configs:
+  - config_name: memory
+    default: true
+    data_files:
+      - split: train
+        path: .memory
+  - config_name: history
+    data_files:
+      - split: train
+        path: .history
+---
+
+# jaimla-loop: Jaimla's improvement loop, as it happened
+
+This is the public record of **improve.skill** for [Jaimla](https://github.com/cryptoAGI/jaimla), the machine learning
+agent: *local first, open door*. Each time a visitor asks her a question on a public Space, the answer is recorded.
+The skill's version counts only the interactions that pass three checks, and **1.0.0 is earned at the 1,000th**.
+Unlike [savante-loop](https://huggingface.co/datasets/PYTHAI/savante-loop), this loop runs **fully automatically**:
+each verified interaction publishes the next version of `SKILL.md`.
+
+This publication is **iteration 8: v0.0.8, 8 of 1,000 verified, 0 refused** (`publication.json`, 2026-09-26).
+
+| file | what it is |
+|---|---|
+| `.memory` | Append-only JSONL. One line per interaction, exactly as it happened, including the engine's own counts. 8 lines. |
+| `.history` | **Derived** from `.memory`, reproducible byte for byte. It holds the interactions that pass the three checks, numbered. Its first line is the summary. |
+| `SKILL.md` | The current skill, v0.0.8: 1,580 bytes, sha256 `eb2fdc50e94bfbc66b4c44c8d8fe0421cd3121dcf16f9b9bfc6e8d4bdb269e0f`. |
+| `history/skill-v0.0.0.md` … `skill-v0.0.7.md` | Each earlier version, archived when the next one was published. |
+| `operator.log` | The operator's edits to the skill, one JSON line each, with the sha256 before and after. |
+| `history/report-2026-09-26.md` | The operator's report on the first four iterations. |
+| `publication.json` | A summary of this publication: the iteration, the road (1,000) and remaining, the skill, the headroom statistics, and the last verified interaction. |
+
+## The three checks
+
+An interaction that fails any check stays in `.memory` and does not count. The checks come from Savante's canon,
+[`bind/skill_history.py`](https://github.com/cryptoAGI/savante/blob/main/bind/skill_history.py):
+
+1. **Single delivery.** `deliveries == 1`.
+2. **Minimum necessary.**
+   - The engine's own counts are present.
+   - The answer ended on its own (`finish == "stop"`).
+   - `completion_tokens <= limit`.
+3. **Minimal improvement.** At most one improvement per interaction, and it must name its evidence.
+
+The version follows the count: 1 → 0.0.1, 100 → 0.1.0, 1000 → 1.0.0. Here `limit` is set by the visitor's
+max-tokens dial (`limit_reason`).
+
+## Audit of this publication (2026-10-08)
+
+Every item below was checked against the files at revision `81a1d977`:
+
+- **`.history` reproduces.** The canon's `skill_history.project`/`render` was run over `.memory`, and its output is
+  identical to `.history`, byte for byte: 8 verified, 0 refused, v0.0.8.
+- **Each interaction ran under an archived skill.** Interaction *n* records the skill it ran under. That is v0.0.*(n−1)*,
+  and its sha256 equals `history/skill-v0.0.(n−1).md` for every *n* from 1 to 8.
+- **The current skill is the published one.** `SKILL.md` has the sha256 and size that `publication.json` names, and its
+  own front matter says `version: 0.0.8`.
+- **The operator's two edits are accounted for exactly.** In `operator.log`, each edit seeds one line into the skill,
+  at v0.0.4 and at v0.0.7:
+  - each archived version's sha256 equals that edit's `sha256_after`;
+  - taking the seeded line out again gives that edit's `sha256_before`.
+- **Every line is complete.** All 8 lines have `deliveries == 1`, `finish == "stop"` and a `response_sha256`. Their ids
+  are unique.
+- **`publication.json` matches.** These values recompute from the files:
+  - `headroom` last 157 and mean 125.5;
+  - `improvements_applied: []`;
+  - `archived_versions: 8`.
+
+## What the record shows
+
+| n | skill | carrier | question | tokens / limit |
+|---|---|---|---|---|
+| 1 | v0.0.0 | Bonsai-8B Q1_0 | Where does my data go when I use you? | 57 / 160 |
+| 2 | v0.0.1 | Bonsai-8B Q1_0 | What can you do on my phone? | 30 / 160 |
+| 3 | v0.0.2 | Bonsai-8B Q1_0 | Where does my data go when I use you? | 29 / 160 |
+| 4 | v0.0.3 | Bonsai-8B Q1_0 | Can you recognise speech offline? | 25 / 160 |
+| 5 | v0.0.4 | Bonsai-8B Q1_0 | Where does my data go when I use you? | 44 / 160 |
+| 6 | v0.0.5 | Ternary-Bonsai-8B Q2_0_g64 | Where does my data go when I use you? | 59 / 160 |
+| 7 | v0.0.6 | Ternary-Bonsai-8B Q2_0_g64 | Can you recognise speech offline? | 29 / 160 |
+| 8 | v0.0.7 | Ternary-Bonsai-8B Q2_0_g64 | Can you recognise speech offline? | 43 / 200 |
+
+- **Carriers.** Every answer came from llama.cpp b11192's `llama-server` on the CPU of the public Space
+  `Gregory-L/mindXhfgradio`. The models are [Bonsai-8B Q1_0](https://huggingface.co/PYTHAI/Bonsai-8B-gguf-fork) (5)
+  and [Ternary-Bonsai-8B Q2_0_g64](https://huggingface.co/PYTHAI/Ternary-Bonsai-8B-gguf-fork) (3), each pinned by
+  sha256.
+- **Where the data goes.** Four times, Bonsai-8B said the visitor's data stays on their device. On this Space that is
+  false. It stayed wrong after the operator seeded the true fact into the skill at v0.0.4.
+- **What changed it.** The first correct answer came at iteration 6, under the seeded skill and on Ternary-Bonsai-8B:
+  "processed on the public Hugging Face Space's CPU … published in my loop". The record can't separate the effect of
+  the new model from the effect of the seed, because both changed together.
+- **Speech offline.** At iteration 8, after the second seed, she named a concrete route: `whisper.cpp` on the user's
+  own device.
+- **No improvements yet.** Every version change so far is either a count or an operator seed. The Learned list has
+  grown only by those two seeds.
+- **Speed.** Answers took between 6.7 s (Bonsai-8B) and 202 s (Ternary-Bonsai-8B) on the shared CPU (`timings`).
+
+## Checking it yourself
+
+**`.history` is reproducible from `.memory`.** Run the canon's `skill_history.py` over this dataset's `.memory`. The
+first line of `.history` names `.claude/skills/sagi/.memory` because that is where the canon's tool reads from:
+
+```sh
+git clone https://github.com/cryptoAGI/savante && cd savante
+cp /path/to/jaimla-loop/.memory .claude/skills/sagi/.memory
+python3 bind/skill_history.py          # "improve.skill v0.0.8: 8 of 1000 verified interactions, 0 refused"
+cmp .claude/skills/sagi/.history /path/to/jaimla-loop/.history && echo identical
+```
+
+**Each archived skill is the one that ran.** `sha256sum history/skill-v*.md`, then compare each with `skill.sha256`
+on the `.memory` line that ran under it.
+
+## Loading it
+
+```python
+from datasets import load_dataset
+memory = load_dataset("json", data_files="hf://datasets/PYTHAI/jaimla-loop/.memory", split="train")
+history = load_dataset("json", data_files="hf://datasets/PYTHAI/jaimla-loop/.history", split="train")
+```
+
+## What this is not
+
+- **Not a benchmark.** These are eight interactions on one public Space.
+- **Published as provenance, not as training data.** It shows how the skill reached its version.
+- **The answers are a 1-bit and a ternary 8B model's, exactly as given.** Several are wrong, and they stay in the record.
+
+## Agent card
+
+Jaimla's ERC-8004 registration card is published with the other sAGI agents' cards in
+[PYTHAI/savante-loop `agents/`](https://huggingface.co/datasets/PYTHAI/savante-loop/tree/main/agents)
+(`jaimla.agentcard.json`, `bafkreifatezacj5yny4phtqezrcmzbmjcrqpai2qj7lqopemfp7pdh4iou`). It is not yet minted.
+
+## Where it comes from
+
+- **Source.** [github.com/cryptoAGI/jaimla](https://github.com/cryptoAGI/jaimla) (the persona and bundle) and
+  `scripts/savante_loop.py` with Savante's `bind/skill_history.py`, as `publication.json` records.
+- **Policy.** "Fully automatic" (operator, 2026-09-26).
+- **Designer.** [Professor Codephreak](https://github.com/Professor-Codephreak). Jaimla → LUV AI → Savante is the sAGI
+  family. Related: [sagi](https://github.com/cryptoAGI/sagi), [bankML](https://github.com/cryptoAGI/bankml).
+
+MIT licence.