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/literature)<a href="https://agentmods.dev/skills/robinslange/learning-loop/literature"><img src="https://agentmods.dev/badge/skills/robinslange/learning-loop/literature/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/literature"><img src="https://agentmods.dev/badge/skills/robinslange/learning-loop/literature.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 | $0.00707 |
| Opus 5.5 | $0.00022 | $0.00283 |
| Sonnet 5.5 | $0.00011 | $0.00141 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
literature 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature: Source Material Capture
Overview
Launches the literature-capturer agent to capture an external source as a literature note. The agent fetches the source, extracts core ideas in persona voice, finds vault connections and counterpoints, verifies claims, and writes to 2-literature/.
When to Use
/literature <URL>: fetch and capture a web source/literature <paper title or citation>: search for and capture an academic source/literature: no argument; asks the user what to capture- When
/deepenflags uncaptured sources worth preserving
Process
Step 0: Parameter Resolution
No argument (/literature):
Use AskUserQuestion:
What source would you like to capture?
- A URL: I'll fetch and extract core ideas
- A paper title or citation: I'll search for it first
Argument provided: Proceed immediately.
Step 1: Launch Agent
Launch the literature-capturer agent with:
- source: The URL, title, or citation provided by the user
- vault_path:
{{VAULT}}/
The agent definition is at ${CLAUDE_PLUGIN_ROOT}/agents/literature-capturer.md (resolve to a literal path before dispatch — see agents-shared/vault-io.md → Placeholders).
Step 2: Handle Backlink Offers
The agent may identify existing vault notes that reference the source without wiki-links. Present these to the user and execute approved edits.
Step 2.5: Replay Post-Write Hooks
The literature-capturer is a subagent. The literature note it wrote to 2-literature/ bypassed PostToolUse, so backlinks and edge inference didn't run. Replay on the returned path:
printf '%s\n' "$LITERATURE_NOTE_PATH" \
| ll-run sweep-hook-replay.mjs --stdin
Where $LITERATURE_NOTE_PATH is constructed from the agent's response (e.g. {{VAULT}}/2-literature/<filename>, where <filename> is the kebab-case filename literature-capturer returned). The backlink edits from Step 2 happen via main-thread Edit and trigger PostToolUse normally: no replay needed for those. See skills-shared/hook-replay.md for the full pattern.
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 · -1 lines 397321a6db6d
- 1mo ago Changed · +1 lines 7710c003bbb4
- 2mo ago First seen · 67 lines · 56 tokens per session scan A ffe045cc06a6
literature 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 707 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.
literature compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| literaturerobinslange/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 |