Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add robinslange/learning-loop/plugin install learning-loopWrote 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/robinslange/learning-loop/deepen)<a href="https://agentmods.dev/skills/robinslange/learning-loop/deepen"><img src="https://agentmods.dev/badge/skills/robinslange/learning-loop/deepen/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/robinslange/learning-loop/deepen"><img src="https://agentmods.dev/badge/skills/robinslange/learning-loop/deepen.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 | $0.01136 |
| Opus 5.5 | $0.00022 | $0.00454 |
| Sonnet 5.5 | $0.00011 | $0.00227 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
deepen 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deepen: Research and Enrichment
Overview
Launches the note-deepener agent to strengthen a single note. The agent assesses maturity, researches gaps scaled to need, rewrites in persona voice, verifies sources, and promotes when ready. Shallow notes get heavy research; deep notes get a light touch.
When to Use
/deepen <note-name>: target a specific note/deepen: no argument; auto-picks the note most in need of work — the shallowest0-inbox/note OR a gate-demoted1-fleeting/note (verification markers /source: unverified) that has no other resurfacing path- When
/inboxflags a note as needing deepening (including the fleeting NEEDS-DEEPEN recommendations) - When a note feels thin and the user wants to strengthen it
Provenance
This skill emits provenance events for pipeline observability. Run each Bash command silently.
At session start:
ll-run provenance-emit.js '{"agent":"deepen","skill":"deepen","action":"session-start","target":"NOTE_FILENAME"}'
At session end. target is a vault path and never exported, so it is dropped here (session-start still carries it, since correlating the run to its note by session_id happens locally, not on the export path). Include the common outcome shape: items_in (1, one note per deepen run), items_out (1 if promoted else 0), items_flagged (0), duration_ms:
ll-run provenance-emit.js '{"agent":"deepen","skill":"deepen","action":"session-end","promoted":true|false,"items_in":1,"items_out":N,"items_flagged":0,"duration_ms":N}'
Per-note tracking is handled automatically by the PostToolUse hook.
Process
Step 0: Parameter Resolution
No argument (/deepen):
Run auto-pick immediately (the agent picks the note most in need of work — the shallowest inbox note OR a gate-demoted marker-bearing 1-fleeting/ note — no prompting needed). After presenting results, mention the targeted form in one line:
Deepened [note]. To target a specific note:
/deepen "note name".
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 Changed 0800ed070afc
- 1mo ago Changed 0e0e3a054a16
- 1mo ago Changed · -2 lines 343912fcf653
- 1mo ago Changed · +2 lines fe45d79242f9
- 2mo ago First seen · 81 lines · 56 tokens per session scan A a6c5080428d5
deepen is a skill published in the GitHub repository robinslange/learning-loop (13 stars, last pushed 4d ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,136 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.
deepen compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deepenrobinslange/learning-loop | Skill | 13 | 4d ago | Apache-2.0 | A | 56 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |