note-scorer

note-scorer is an agent for Claude Code from robinslange/learning-loop. It costs 33 tokens per session (2,085 once invoked), scanned A, original, Apache-2.0.

A batch reviewer for notes in an Obsidian vault, a folder of linked Markdown notes. It scores how developed and well-supported each note is, then recommends an action.

In plain words
What is it for?
Use it to assess selected notes, score claim specificity and source support, assign maturity levels, and recommend what to do next.
Why use it?
It gives notes a consistent quality check, making it easier to decide which ideas need sources, clearer claims, or further development.

Agent for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: model in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the learning-loop plugin — 24 skills, 20 agents, 7 hooks shipped together

Good fit Use it to assess selected notes, score claim specificity and source support, assign maturity levels, and recommend what to do next.

Compare 6 agents from other repositories ↓
Install

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.

Claude Code
/plugin marketplace add robinslange/learning-loop
Claude Code
/plugin install learning-loop

Made for: Claude Code.

Or install learning-loop, the plugin that ships this one along with the rest of its 24 skills, 20 agents, 7 hooks.

Wrote 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.

agentmods badge for note-scorer

README.md
[![agentmods](https://agentmods.dev/badge/agents/robinslange/learning-loop/note-scorer/github.svg)](https://agentmods.dev/agents/robinslange/learning-loop/note-scorer)
Your own site
<a href="https://agentmods.dev/agents/robinslange/learning-loop/note-scorer"><img src="https://agentmods.dev/badge/agents/robinslange/learning-loop/note-scorer/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.

agentmods 80×15 button for note-scorer

Your own site · 80×15
<a href="https://agentmods.dev/agents/robinslange/learning-loop/note-scorer"><img src="https://agentmods.dev/badge/agents/robinslange/learning-loop/note-scorer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,085 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.02085
Opus 5.5 $0.00013 $0.00834
Sonnet 5.5 $0.00007 $0.00417
Haiku 4.5 $0.00003 $0.00209

Measured 1mo ago against content hash 438211af13b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

plugin/agents/note-scorer.md · 157 lines

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

  1. Read the promote-gate skill.
  2. Read each note using the Read tool.
  3. Run the promote-gate pass/fail assessment (6 criteria). For [synthesis]-tagged notes, Sourcing and Source Integrity are exempt -- assess on the remaining 4.
  4. Score the two orthogonal dimensions from promote-gate scoring mode: claim_specificity (0-2) and source_grounded (0-2).
  5. Derive maturity tier from the note-level score (shallow < 0.4, medium 0.4-0.7, deep > 0.7).
  6. Recommend an action.

For linking assessment, use ll-run 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 |

Read the full file on GitHub · 157 lines

Changes

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.

  1. 1mo ago Changed 438211af13b6
  2. 1mo ago Changed · -1 lines 6944fc90462c
  3. 1mo ago Changed · +1 lines cf1fae7663c1
  4. 2mo ago First seen · 157 lines · 33 tokens per session scan A b2846f0dea7b

Subscribe to this mod's changes

note-scorer is an agent published in the GitHub repository robinslange/learning-loop (13 stars, last pushed 4d ago), licensed Apache-2.0. It adds 33 tokens to every session and 2,085 once invoked, about $0.0001 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.

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