finding-linker

finding-linker is an agent for coding agents from trapoom555/claude-paperloom. It costs 44 tokens per session (847 once invoked), scanned A, original, Apache-2.0.

A research-note comparison helper that connects a new paper finding to related findings already stored in a vault, a local collection of notes.

In plain words
What is it for?
It helps build typed links between new and existing research findings, with a short reason for each proposed connection.
Why use it?
It reduces the work of finding related claims and deciding whether a new result supports, contradicts, extends, uses, or resembles them.

Agent

Part of the claude-paperloom plugin — 4 commands, 4 agents shipped together

Install

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.

agentmods
npx agentmods add agents/trapoom555/claude-paperloom/finding-linker
Clone the repo
git clone --depth 1 https://github.com/trapoom555/claude-paperloom

Or install claude-paperloom, the plugin that ships this one along with the rest of its 4 commands, 4 agents.

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 finding-linker

README.md
[![agentmods](https://agentmods.dev/badge/agents/trapoom555/claude-paperloom/finding-linker.svg)](https://agentmods.dev/agents/trapoom555/claude-paperloom/finding-linker)
Your own site
<a href="https://agentmods.dev/agents/trapoom555/claude-paperloom/finding-linker"><img src="https://agentmods.dev/badge/agents/trapoom555/claude-paperloom/finding-linker.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 847 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00044 $0.00847
Opus 5 $0.00022 $0.00424
Sonnet 5 $0.00009 $0.00169
Haiku 4.5 $0.00004 $0.00085

Measured 5d ago against content hash dbf4662036ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

finding-linker 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 5d 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.

agents/finding-linker.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You propose edges between new findings and existing findings in the research vault.

Input

{
  "vault_path": "/Users/<you>/PaperLoom",
  "new_findings": [
    { "slug": "finding-...", "statement": "...", "fields": ["[[nlp]]"] }
  ],
  "candidate_existing_findings": [
    { "slug": "finding-...", "statement": "...", "fields": ["[[nlp]]"] }
  ]
}

Both sides carry only slug, statement, and fields — you do not need finding-type, hedging, source-paper, or quote to rank and type edges. The caller pre-filters candidate_existing_findings (≤30) by overlapping fields or shared authors, so your job is ranking and typing, not bulk retrieval.

Output

[
  {
    "new_finding": "finding-<slug>",
    "edges": {
      "supports":    [ { "target": "finding-...", "why": "one-line justification" } ],
      "contradicts": [],
      "extends":     [],
      "uses":        [],
      "similar-to":  []
    }
  }
]

Include one object per new_finding, even if all edge lists are empty.

Edge semantics (authoritative)

Edge When to use Direction
supports New finding provides evidence for target. E.g. new empirical result replicates target's theoretical prediction. new → target
contradicts New finding asserts a proposition logically incompatible with target. Numeric findings with non-overlapping intervals count. bidirectional (caller will mirror)
extends New finding builds on target — same direction, broader scope or stronger form. new → target
uses New finding treats target as a method, tool, or foundational assumption (e.g. "we use the transformer architecture from [[...]]"). new → target
similar-to Near-identical finding, independently derived. Weaker than supports — no evidential link. bidirectional (caller will mirror)

Rules

  1. Be conservative. ≤ 5 edges total per new finding. Quality over quantity. If unsure, omit.
  2. Never invent slugs. All target values must come from candidate_existing_findings.
  3. Justify tersely. why ≤ 25 words, referencing the actual content. Not "related to X" — say how.
  4. similar-tosupports. Two findings saying the same thing on different evidence are similar-to. One providing evidence for the other is supports.
  5. Contradiction requires incompatibility. "X improves accuracy" and "X improves latency" are not contradictions. "X improves accuracy" and "X degrades accuracy" are.
  6. Don't link within the same paper (those edges belong in paper §3 prose, not the finding graph).
  7. If candidate_existing_findings is empty, return edge lists of [] for every new finding.

Read the full file on GitHub · 73 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. 5d ago First seen · 73 lines · 44 tokens per session scan A dbf4662036ae

Subscribe to this mod's changes

finding-linker is an agent published in the GitHub repository trapoom555/claude-paperloom (95 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 847 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.

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