assess-ip-landscape

assess-ip-landscape is a skill for Claude Code from pjt222/agent-almanac. It costs 93 tokens per session (2,526 once invoked), scanned A, original, MIT.

An intellectual-property landscape study for a technology or product area. It examines patents, competing portfolios, unclaimed areas, and preliminary freedom-to-operate risks; freedom to operate means checking whether a product may infringe existing rights.

In plain words
What is it for?
Use it to guide research plans, assess competitors’ patents, prepare investment due diligence, plan patent filings, or screen risks for a new product.
Why use it?
It helps reveal legal and competitive constraints before investing in research, entering a market, or filing patents. It also highlights gaps and possible strategic positions.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the agent-almanac plugin — 122 skills, 76 agents shipped together

Good fit Use it to guide research plans, assess competitors’ patents, prepare investment due diligence, plan patent filings, or screen risks for a new product.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pjt222/agent-almanac/assess-ip-landscape
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.

Any agent
npx skills add pjt222/agent-almanac --skill assess-ip-landscape
Clone the repo
git clone --depth 1 https://github.com/pjt222/agent-almanac

Made for: Claude Code.

Or install agent-almanac, the plugin that ships this one along with the rest of its 122 skills, 76 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 assess-ip-landscape

README.md
[![agentmods](https://agentmods.dev/badge/skills/pjt222/agent-almanac/assess-ip-landscape/github.svg)](https://agentmods.dev/skills/pjt222/agent-almanac/assess-ip-landscape)
Your own site
<a href="https://agentmods.dev/skills/pjt222/agent-almanac/assess-ip-landscape"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/assess-ip-landscape/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.

agentmods 80×15 button for assess-ip-landscape

Your own site · 80×15
<a href="https://agentmods.dev/skills/pjt222/agent-almanac/assess-ip-landscape"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/assess-ip-landscape.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,526 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00093 $0.02526
Opus 5 $0.00046 $0.01263
Sonnet 5 $0.00019 $0.00505
Haiku 4.5 $0.00009 $0.00253

Measured 8d ago against content hash 784bd18a2f69, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

assess-ip-landscape 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 8d 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.

i18n/caveman-lite/skills/assess-ip-landscape/SKILL.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assess IP Landscape

Map the intellectual property landscape for a technology area — identify patent clusters, white spaces, key players, and freedom-to-operate risks. Produces a strategic assessment that informs R&D direction, licensing decisions, and IP filing strategy.

When to Use

  • Before starting R&D in a new technology area (what's already claimed?)
  • Evaluating a market entry where incumbents have strong patent portfolios
  • Preparing for investment due diligence (IP asset assessment)
  • Informing a patent filing strategy (where to file, what to claim)
  • Assessing freedom-to-operate risk for a new product or feature
  • Monitoring competitor IP activity for strategic positioning

Inputs

  • Required: Technology domain or product area to assess
  • Required: Geographic scope (US, EU, global)
  • Optional: Specific competitors to focus on
  • Optional: Own patent portfolio (for gap analysis and FTO)
  • Optional: Time horizon (last 5 years, last 10 years, all time)
  • Optional: Classification codes (IPC, CPC) if known

Procedure

Step 1: Define the Search Scope

Establish the boundaries of the landscape analysis.

  1. Define the technology domain precisely:
    • Core technology area (e.g., "transformer-based language models" not "AI")
    • Adjacent areas to include (e.g., "attention mechanisms, tokenization, inference optimization")
    • Areas to explicitly exclude (e.g., "computer vision transformers" if focusing on NLP)
  2. Identify relevant classification codes:
    • IPC (International Patent Classification) — broad, used worldwide
    • CPC (Cooperative Patent Classification) — more specific, US/EU standard
    • Search WIPO's IPC publication or USPTO's CPC browser
  3. Define the geographic scope:
    • US (USPTO), EU (EPO), WIPO (PCT), specific national offices
    • Most analyses start with US + EU + PCT for broad coverage
  4. Set the time window:
    • Recent activity: last 3-5 years (current competitive landscape)
    • Full history: 10-20 years (mature technology areas)
    • Watch for expired patents that open up design space
  5. Document the scope as the Landscape Charter

Read the full file on GitHub · 215 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. 8d ago First seen · 215 lines · 93 tokens per session scan A 784bd18a2f69

Subscribe to this mod's changes

assess-ip-landscape is a skill published in the GitHub repository pjt222/agent-almanac (32 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 2,526 once invoked, about $0.0005 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.