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 docxology/template --skill continual-learninggit clone --depth 1 https://github.com/docxology/templateWrote 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/docxology/template/continual-learning)<a href="https://agentmods.dev/skills/docxology/template/continual-learning"><img src="https://agentmods.dev/badge/skills/docxology/template/continual-learning/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/docxology/template/continual-learning"><img src="https://agentmods.dev/badge/skills/docxology/template/continual-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00056 | $0.00293 |
| Opus 5.5 | $0.00022 | $0.00117 |
| Sonnet 5.5 | $0.00011 | $0.00059 |
| Haiku 4.5 | $0.00006 | $0.00029 |
Grade A, and why
continual-learning 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 1mo 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.
What it actually says
Continual Learning (template repo)
Keep durable agent memory in local JSON, not in root AGENTS.md.
Trigger
Use when the user asks to mine prior chats, maintain agent memory, or run the continual-learning loop (including stop-hook followups).
Workflow
- Call the
agents-memory-updatersubagent (repo override at.cursor/agents/agents-memory-updater.md). - Return the updater result verbatim.
Target file
- Memory:
.cursor/hooks/state/continual-learning-memory.json - Schema example:
.cursor/hooks/state/continual-learning-memory.example.json - Optional helpers:
infrastructure.core.agent_memory
Guardrails
- Keep this skill orchestration-only — do not mine transcripts or edit files in the parent flow.
- Do not bypass the subagent.
- Never add or edit
## Learned User Preferencesor## Learned Workspace Factsin rootAGENTS.md(public-repo contract). - Do not commit
continual-learning-memory.jsonorcontinual-learning-index.json.
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.
- 1mo ago First seen · 32 lines · 56 tokens per session scan A abd950dc5328
continual-learning is a skill published in the GitHub repository docxology/template (20 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 293 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
learn
Review the current conversation and update project knowledge artifacts - common-gotchas.md (bug patterns), conventions at the highest rung that holds them (code, check, reviewer standard, skill, then AGENTS.md), navigation pointers, agent memory (cross-session). Use when asked to '/learn', 'what did we learn'…
save-learning
Use when you learned something durable — a decision, a hard-won lesson, a useful reference. Captures it into the memory wiki so it compounds.
kiro-steering-custom
Create custom steering documents for specialized project contexts.
memory
Cross-project research memory. Deep-dive past projects' notes, record corrections, and save cross-project insights across all Luxas research projects.
daily-journal
A passive daily work journal that Claude keeps FOR you so you never have to write it yourself. Append short entries after meaningful work (what was done, what you focused on, artifacts touched) to 01-daily/journal/YYYY-MM-DD.md. Run a guided reflection at night or in the morning. Use when you run /daily-journal, say…
honey-memory
Per-project persistent memory files indexed in MEMORY.md.