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 skills add LigphiDonk/Oh-my--paper --skill inno-prepare-resourcesgit clone --depth 1 https://github.com/LigphiDonk/Oh-my--paperWrote 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/ligphidonk/oh-my--paper/inno-prepare-resources)<a href="https://agentmods.dev/skills/ligphidonk/oh-my--paper/inno-prepare-resources"><img src="https://agentmods.dev/badge/skills/ligphidonk/oh-my--paper/inno-prepare-resources/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/ligphidonk/oh-my--paper/inno-prepare-resources"><img src="https://agentmods.dev/badge/skills/ligphidonk/oh-my--paper/inno-prepare-resources.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 188 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00041 | $0.03181 |
| Opus 5 | $0.00020 | $0.01590 |
| Sonnet 5 | $0.00008 | $0.00636 |
| Haiku 4.5 | $0.00004 | $0.00318 |
Grade A, and why
inno-prepare-resources 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 11d 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 — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
inno-prepare-resources
Canonical Summary
Loads the evaluation instance, searches GitHub for related repositories, builds a dataset description, queries the Prepare Agent for reference codebases, and downloads arXiv paper sources. Covers both Idea mode and Plan mode (the only diff...
Trigger Rules
Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.
Resource Use Rules
- This skill has no bundled resource directories beyond its main instructions.
Execution Contract
- Resolve every relative path from this skill directory first.
- Prefer inspection before mutation when invoking bundled scripts.
- If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
- Do not write generated artifacts back into the skill directory; save them inside the active project workspace.
Upstream Instructions
Inno Prepare Resources
Inputs
Read from instance.json. Path values are absolute when the project is created by Dr. Claw; use as-is. If relative (e.g. hand-edited), resolve with path.join(project_path, value).
| Parameter | Required | Description |
|---|---|---|
instance |
Yes | Path to the instance JSON file (absolute in Dr. Claw). Use as-is to read the file. File contains source_papers, task1/task2, etc. |
task_level |
Yes | Which task field to read from the instance — "task1" (Plan) or "task2" (Idea) |
Ideation.references |
Yes | Path to Ideation references dir (absolute in Dr. Claw) — for downloaded papers and prepare logs |
Experiment.code_references |
Yes | Path (absolute in Dr. Claw) — for cloned repos |
Experiment.datasets |
Yes | Path (absolute in Dr. Claw) — for dataset files |
category |
Yes | Research category tag (e.g. nlp_qa, gnn, recommendation). Used to locate the built-in dataset metaprompt |
references |
Yes | A pre-formatted string listing all source papers from the instance |
context_variables |
Yes | Shared context dictionary; this step will write date_limit into it |
ideas |
No | Full innovative-idea / plan text. Provide only in Plan mode — when present the Prepare Agent query includes the ideas for more targeted repo selection |
dataset_description |
No | Pre-built dataset description from the orchestrator (for custom / user-provided datasets). When provided, skip the metaprompt import in Step 3 |
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.
- 11d ago First seen · 313 lines · 41 tokens per session scan A 537b07282dd3
inno-prepare-resources is a skill published in the GitHub repository LigphiDonk/Oh-my--paper (722 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 3,181 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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