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 trapoom555/claude-paperloom/plugin install claude-paperloomWrote 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/commands/trapoom555/claude-paperloom/ingest)<a href="https://agentmods.dev/commands/trapoom555/claude-paperloom/ingest"><img src="https://agentmods.dev/badge/commands/trapoom555/claude-paperloom/ingest.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.02695 |
| Opus 5 | $0.00018 | $0.01347 |
| Sonnet 5 | $0.00007 | $0.00539 |
| Haiku 4.5 | $0.00004 | $0.00269 |
Grade A, and why
ingest 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 6d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/paperloom:ingest
Fast, triage-grade ingest. $ARGUMENTS is the paper reference.
Division of labor: the deterministic steps (fetch, parse, template fill, edge aggregation, logging, stub creation, citation matching) are done by Python scripts in ${CLAUDE_PLUGIN_ROOT}/scripts/. The LLM is used only for the three remaining semantic subagents: lite-drafter, finding-extractor, metadata-extractor. Per-item LLM loops are forbidden — if you find yourself running an agent N times for N items, stop and shell out to a script.
Step 0 — greet the user
Print exactly:
📖 Ingesting your paper — this will take a moment. Sit back, get cozy, and maybe grab a coffee ☕️
Step 1 — fetch + extract
Shell out. The script validates the vault, classifies the input, caches the raw file, and produces full + brief text:
"${CLAUDE_PLUGIN_ROOT}/.venv/bin/python3" "${CLAUDE_PLUGIN_ROOT}/scripts/fetch_paper.py" "<vault-path>" "$ARGUMENTS"
Parse the JSON result.
Early exit — duplicate paper. If the result has "already_exists": true, the paper is already in the vault (matched by arxiv-id, doi, or source-url). Do not run any further steps. Print a short message naming the existing slug, e.g.:
⏭️ This paper is already in your vault as
papers/<existing.slug>.md— skipping ingest.
Then stop.
Otherwise, keep full_text_path, brief_text_path, findings_text_path, meta_text_path, source_url, arxiv_id, doi for later steps.
Step 2 — scan vault for context
Run these in parallel (they're independent reads):
"${CLAUDE_PLUGIN_ROOT}/.venv/bin/python3" "${CLAUDE_PLUGIN_ROOT}/scripts/vault_scan.py" fields "<vault-path>"
"${CLAUDE_PLUGIN_ROOT}/.venv/bin/python3" "${CLAUDE_PLUGIN_ROOT}/scripts/vault_scan.py" papers "<vault-path>"
"${CLAUDE_PLUGIN_ROOT}/.venv/bin/python3" "${CLAUDE_PLUGIN_ROOT}/scripts/vault_scan.py" authors "<vault-path>"
Hold the outputs: existing_fields, vault_papers, existing_authors.
Step 3 — fan-out: 2 LLM subagents (semantic-only)
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.
- 6d ago First seen · 241 lines · 36 tokens per session scan A b5ea7e12cd13
ingest is a command published in the GitHub repository trapoom555/claude-paperloom (95 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 2,695 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.