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 markoblogo/abvx-agent-skills --skill agent-learning-layer-triagegit clone --depth 1 https://github.com/markoblogo/abvx-agent-skillsWrote 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/markoblogo/abvx-agent-skills/agent-learning-layer-triage)<a href="https://agentmods.dev/skills/markoblogo/abvx-agent-skills/agent-learning-layer-triage"><img src="https://agentmods.dev/badge/skills/markoblogo/abvx-agent-skills/agent-learning-layer-triage/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/markoblogo/abvx-agent-skills/agent-learning-layer-triage"><img src="https://agentmods.dev/badge/skills/markoblogo/abvx-agent-skills/agent-learning-layer-triage.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 | $0.00066 | $0.01017 |
| Opus 5 | $0.00033 | $0.00508 |
| Sonnet 5 | $0.00013 | $0.00203 |
| Haiku 4.5 | $0.00007 | $0.00102 |
Grade A, and why
agent-learning-layer-triage 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 9d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Learning Layer Triage
Use this skill when a task produces a lesson and the next question is: where should this learning live?
ABVX does not assume the model itself learns. Most useful operational learning belongs in an auditable layer around the model: context, skills, scripts, gates, and evals.
Learning Layers
Classify the candidate into the cheapest durable layer that solves the repeated problem:
- Leave as prompt/session behavior: one-off correction, low recurrence, no durable value.
- Memory or context note: stable preference, repo fact, operator convention, or short reminder that should be easy to read and revise.
- Durable repo doc: stable repo architecture, setup, verification, deployment, or workflow fact that future agents must discover reliably.
- Checklist: repeated human or agent sequence where order matters but no portable behavior layer is needed yet.
- SKILL.md: reusable behavior with a clear trigger, action rules, anti-patterns, and verification discipline.
- Script or tool: deterministic repeated step where code is more reliable than prose.
- Eval or golden fixture: behavior must be regression-tested, especially after a bug, review failure, or model drift.
- Reject / park: plausible but overfit, too broad, not validated, duplicative, or unsafe.
Prefer the lowest layer that makes the next run materially better.
Triage Questions
Ask in order:
- Did this happen more than once, or is recurrence likely?
- Is the lesson stable across repos, or only local to one repo/session?
- Is the value factual recall, procedural behavior, deterministic execution, or regression detection?
- Can the lesson be verified by a command, fixture, review rubric, or before/after trace?
- Would adding this to always-loaded context increase startup cost more than it reduces future mistakes?
- Does it duplicate a stronger existing skill, script, doc, or higher-priority instruction?
- Could it weaken a safety, trust, authorization, privacy, or destructive-action boundary?
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.
- 9d ago First seen · 88 lines · 66 tokens per session scan A ce100babd5d8
agent-learning-layer-triage is a skill published in the GitHub repository markoblogo/abvx-agent-skills (16 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 1,017 once invoked, about $0.0003 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 2026-08-30.
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