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 yogsoth-ai/de-anthropocentric-research-engine --skill competitive-intelligencegit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/yogsoth-ai/de-anthropocentric-research-engine/competitive-intelligence)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/competitive-intelligence"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/competitive-intelligence/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/yogsoth-ai/de-anthropocentric-research-engine/competitive-intelligence"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/competitive-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 119 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00034 | $0.01302 |
| Opus 5 | $0.00017 | $0.00651 |
| Sonnet 5 | $0.00007 | $0.00260 |
| Haiku 4.5 | $0.00003 | $0.00130 |
Grade A, and why
competitive-intelligence 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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Intelligence
Analyzes competitor patent portfolios to infer R&D strategy, identify strengths and weaknesses, and produce comparative intelligence reports.
Purpose
Profile competitor IP portfolios to understand their technology focus, filing strategy, geographic coverage, and potential future directions. Enables strategic IP positioning.
Budget
| Metric | Target |
|---|---|
| Patent families analyzed | 120 |
| Claim parses | 15 |
| Web searches completed | 40 |
State Ledger
| Metric | Target | Current | % |
|---|---|---|---|
| Patent families analyzed | 120 | 0 | 0% |
| Claim parses completed | 15 | 0 | 0% |
| Web searches completed | 40 | 0 | 0% |
| Competitors profiled | — | 0 | — |
| Portfolio comparisons | — | 0 | — |
HARD-GATE: Cannot exit iteration loop until 80% of patent families (96), claim parses (12), and web searches (32) budget met.
Available Tactics
| Tactic | When to Use |
|---|---|
| patent-family-tracing | Build complete portfolio for each competitor |
| classification-navigation | Map competitor technology focus areas |
| claim-decomposition | Analyze claim scope of competitor key patents |
Available SOPs
| SOP | Role in This Strategy |
|---|---|
| patent-query-formulation | Generate assignee-focused search queries |
| assignee-normalization | Resolve subsidiary/parent relationships |
| patent-categorization | Classify competitor patents by technology area |
| citation-network-analysis | Map inter-competitor citation relationships |
| trend-analysis | Analyze competitor filing velocity and direction |
| claim-parsing | Parse key competitor claims for scope analysis |
| quality-scoring | Assess competitor patent quality distribution |
| legal-status-assessment | Determine active vs. expired competitor IP |
| saturation-detection | Confirm portfolio coverage is complete |
| patent-synthesis | Produce competitive intelligence report |
Execution Guidance
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.
- 5d ago First seen · 149 lines · 34 tokens per session scan A 83c0eb4f9700
competitive-intelligence is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (444 stars, last pushed today), licensed Apache-2.0. It adds 34 tokens to every session and 1,302 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 2026-09-03.
Other skills, from other repositories
patent-disclosure-skill
A Chinese patent-work assistant for finding invention ideas, writing patent disclosures, explaining patents in plain language, tracking policy changes, and preparing responses to examiner notices.
patent-search
A search tool for published Chinese patent records, using fields such as inventor, applicant, classification number, and title.
patent-disclosure
A guided workflow for finding patentable ideas, doing a limited prior-art search, and drafting a Chinese patent disclosure document. A disclosure document describes an invention for later patent drafting.
patent-application
A patent-application document workflow that turns supplied invention materials into claims, a description, an abstract, and black-and-white drawings. It can also produce Markdown and Word files.
Deep Research
Produce a deep, structured research report on a topic: decompose into key dimensions, analyze each with evidence and reasoning, synthesize cross-cutting insights, and surface open questions. Use for deep research, analysis, and literature/landscape reviews.
omnisci
Run OmniScientist end to end in the OmniScientist CLI using DeepSeek V4 Flash. Turn raw research data (images, signals, audio, video, 3-D, tables, or graphs) and an open direction into perceived evidence, a falsifiable hypothesis, recorded analysis, real citations, a gated candidate paper, PDF, and Overleaf bundle.…