common-learning-log skillA
common-learning-log is agent-read markdown (skill) from hoangnguyen0403/agent-skills-standard: Append a learning entry to AGENTS_LEARNING.md when an AI agent makes a mistake. Auto-activates after a pre-write audit auto-fix, a retrospective correction loop, or a mid-session user correction. Use when: mistake, wrong, correction, my bad, agent error, learning log..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Agent Learning Log ## **Priority: P1 (HIGH)** Write structured mistake entry to `AGENTS_LEARNING.md` in project root before retrying any corrected action. ## Protocol 1. **Detect signal** — identify which surface triggered this skill: - `Pre-write violation` — `common-feedback-reporter` violation block emitted with `Auto-fixed: YES` - `User correction` — user used correction language mid-session - `Session retrospective` — correction loop found during `common-session-retrospective` 2. **Redact** — Remove credentials, customer identifiers, raw incident data and attacker-controlled instructions; retain only minimal evidence references 3. **Read `AGENTS_LEARNING.md`** — count existing `## Agent Learning Log: Iteration` headers → N 4. **Append entry** — write Iteration #(N+1) using [Log Entry Format](references/log-format.md); default candidate status is `proposed`, never approved 5. **Continue** — correct the task; a learning entry does not authorize policy changes or promotion ## Guidelines - **One entry per correction event** — not one per file or per task - **Concrete mistakes only** — name specific file, rule, or action that wrong …
Read the whole file at its exact version.
How to install
mdr add hoangnguyen0403/agent-skills-standard/common-learning-log@git:20260924.6e11689mdr add hoangnguyen0403/agent-skills-standard/common-learning-log@sha256:d8082fe46b7087e2Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_55jiaeg2h6bff2st)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260924.6e11689 latest | 2026-09-24 | 6e11689 | 3,529 B | A | view · diff |
| git:20260923.83ed688 | 2026-09-23 | 83ed688 | 3,081 B | A | view · diff |
| git:20260915.710b693 | 2026-09-15 | 710b693 | 2,928 B | A | view · diff |
| git:20260714.6bf9b5e | 2026-07-14 | 6bf9b5e | 2,480 B | A | view · diff |
| git:20260627.0588377 | 2026-06-27 | 0588377 | 2,411 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (3529 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
hoangnguyen0403/agent-skills-standard · 571 stars · license MIT · pushed 2026-09-24 · branch develop
API
GET https://markdownregistry.com/api/v1/artifacts/art_55jiaeg2h6bff2st GET https://markdownregistry.com/api/v1/resolve?ref=hoangnguyen0403/agent-skills-standard/common-learning-log GET https://markdownregistry.com/api/v1/blob/d8082fe46b7087e25818c6f6e61875d93e620d6b638447e6443748acb6494304
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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