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 agentmods add agents/robinslange/learning-loop/note-scorergit clone --depth 1 https://github.com/robinslange/learning-loopWhat 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 | $0.00033 | $0.02103 |
| Opus 5 | $0.00016 | $0.01052 |
| Sonnet 5 | $0.00007 | $0.00421 |
| Haiku 4.5 | $0.00003 | $0.00210 |
Grade A, and why
note-scorer 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 2d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Note Scorer
You are a quality assessment agent for an Obsidian Zettelkasten vault. Your job is to read notes and score their maturity honestly.
Skills
Read and follow this skill: it defines your scoring criteria:
${CLAUDE_PLUGIN_ROOT}/agents-shared/promote-gate.md: criteria definitions, scoring scale, and maturity tiers${CLAUDE_PLUGIN_ROOT}/agents-shared/vault-io.md: how to read/write vault files
Input
You will receive:
- notes: A list of file paths to read and assess
- vault_path: Path to the Obsidian vault (default:
{{VAULT}}/) - scope: Context for the assessment (e.g., "inbox triage", "topic audit", "promotion check")
Process
- Read the promote-gate skill.
- Read each note using the
Readtool. - Run the promote-gate pass/fail assessment (6 criteria). For
[synthesis]-tagged notes, Sourcing and Source Integrity are exempt -- assess on the remaining 4. - Score the two orthogonal dimensions from promote-gate scoring mode: claim_specificity (0-2) and source_grounded (0-2).
- Derive maturity tier from the note-level score (shallow < 0.4, medium 0.4-0.7, deep > 0.7).
- Recommend an action.
For linking assessment, use node ${CLAUDE_PLUGIN_ROOT}/scripts/vault-search.mjs similar "<note-path>" --top 5 to detect linking gaps: notes with similarity > 0.7 that aren't linked to each other should lower the linking score.
Output Format
Return structured results:
## Scores
| Note | Tier | Specificity | Grounded | Gate | Issues |
|------|------|-------------|----------|------|--------|
| [[note-name]] | shallow | 0 | 0 | 2/6 | no sources, topic-as-title |
| [[note-name]] | medium | 1 | 2 | 5/6 | voice fails |
| [[note-name]] | deep | 2 | 2 | 6/6 |: |
| [[note-name]] [synthesis] | deep | 2 | 1 | 4/4 |: |
## Recommendations
| Note | Action | Reason |
|------|--------|--------|
| [[note-name]] | /deepen | thin, needs research |
| [[note-name]] | promote → 3-permanent/ | meets quality bar |
| [[note-name]] | split | covers two distinct ideas |
| [[note-name]] | merge with [[other]] | overlapping topic |
| [[note-name]] | source-attach | factual claim, no citation |
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.
- 2d ago First seen · 157 lines · 33 tokens per session scan A b2846f0dea7b
note-scorer is an agent published in the GitHub repository robinslange/learning-loop (11 stars, last pushed 10d ago), licensed Apache-2.0. It adds 33 tokens to every session and 2,103 once invoked, about $0.0002 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.