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 raja21068/AutoResearch --skill invention-structuringgit clone --depth 1 https://github.com/raja21068/AutoResearchWrote 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/raja21068/autoresearch/invention-structuring)<a href="https://agentmods.dev/skills/raja21068/autoresearch/invention-structuring"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/invention-structuring/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/raja21068/autoresearch/invention-structuring"><img src="https://agentmods.dev/badge/skills/raja21068/autoresearch/invention-structuring.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00056 | $0.01465 |
| Opus 5 | $0.00028 | $0.00732 |
| Sonnet 5 | $0.00011 | $0.00293 |
| Haiku 4.5 | $0.00006 | $0.00146 |
Grade A, and why
invention-structuring 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 7d 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.
This is a copy
92% identical to invention-structuring — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Invention Structuring
Structure the invention into a formal disclosure based on: $ARGUMENTS
Adapted from the refinement pattern in /research-refine for patent invention decomposition.
Constants
REVIEWER_MODEL = gpt-5.4— External reviewer for invention decomposition validationMAX_REFINEMENT_ROUNDS = 3— Maximum structuring iterations
Inputs
- Invention description from
$ARGUMENTS patent/INVENTION_BRIEF.mdif existspatent/PRIOR_ART_REPORT.md— prior art landscapepatent/NOVELTY_ASSESSMENT.md— novelty analysis
Shared References
Load ../shared-references/patent-writing-principles.md for the Problem-Solution-Advantage framework and claimable subject matter guidelines.
Workflow
Step 1: Problem-Solution-Advantage Framework
Structure the invention using the universal patent framework:
Technical Problem (要解决的技术问题):
- Derived from prior art deficiencies identified in NOVELTY_ASSESSMENT.md
- Must be a specific, technical problem (not a commercial or social problem)
- Statement format: "The technical problem to be solved is how to [specific technical objective] given [specific technical constraint]."
Technical Solution (技术方案):
- The invention's specific technical contribution
- Focus on the mechanism, not the result
- Must be described at a level that matches the intended claim scope
- Identify which features are known vs. inventive
Advantages (有益效果):
- Measurable or quantifiable improvements over prior art
- Must result from the inventive features, not just good engineering
- Include specific technical effects if known (e.g., "reduces processing time by 40%")
Step 2: Invention Decomposition
Break the invention into three layers:
Core Inventive Concept (核心发明构思):
- The minimal set of features that make the invention patentable
- This maps to the independent claim scope
- Test: if you remove this feature, the invention is no longer novel
Supporting Features (支撑性特征):
- Features that make the invention work well in practice
- These become dependent claim material
- They narrow the scope but add practical value
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.
- 7d ago First seen · 188 lines · 56 tokens per session scan A 10993307f071
invention-structuring is a skill published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 1,465 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to invention-structuring, differing in 7 lines, and is treated as a copy.
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