Assess High Value Patent Portfolio Ip

Assess a High-Value Patent Portfolio

Overview

Use this skill to turn one reviewed Patsnap patent query into a transparent, reproducible portfolio-screening package. Retrieve the full agreed candidate universe, enrich every candidate for scoring, apply the source 30/30/20/20 model, select a documented 10–15%, and preserve all evidence and failures.

The term high-value describes relative selection under this model. It does not mean monetary value, commercial success, technical quality, validity, enforceability, freedom to operate, essentiality, or investment merit.

Never fabricate a patent record, citation, family member, inventor identity, legal event, legal status, drawing, technical summary, score, source link, or missing API result. An endpoint failure stays error; a missing field stays missing; neither becomes factual zero.

When to use

Use this skill when the user asks to:

• identify a high-value subset within a patent search result;
• rank a portfolio or technology-specific candidate universe;
• create a traceable patent-prioritization list;
• apply the explicit citation/family/inventor/event model;
• compare screening signals across patents in one scoped run; or
• prepare a portfolio review for an analyst, IP team, R&D leader, or counsel.

Do not use it as the sole method for:

• patent valuation or pricing;
• validity, infringement, enforceability, or FTO opinions;
• standards-essentiality or claim-chart determinations;
• acquisition or investment recommendations; or
• comparisons between independently scoped query results.

Required inputs

Obtain or explicitly mark missing:

1. The exact, human-reviewed Patsnap query.
2. The legal entities, technologies, products, and exclusions represented by the query.
3. Target jurisdictions or authorities.
4. Search and legal-status cutoff dates.
5. Date range and publication/application/grant treatment.
6. Family definition and representative-publication rule.
7. Screening purpose and intended audience.
8. Candidate cap, if any, and whether truncation is acceptable.
9. Selection ratio between 10% and 15%; default 10%.
10. Any reviewed core-inventor override.
11. Any user-approved weight change. If changed, do not describe the result as the default source model.
12. Required report language; default English.

Do not silently broaden, narrow, translate, repair, or reformulate the query. If a generated query is proposed, require human approval before execution and record both the draft and approved query.

Required deliverables

Always produce:

• high_value_patent_portfolio_screening.html — safe static English report;
• high_value_patent_screening_data.json — all scored candidates plus selected records and evidence trace;
• final_records.json — selected report-ready records;
• restartable stage checkpoints described below.

Produce only when the user requests Word:

• high_value_patent_portfolio_screening.docx — same substantive selection, scores, rationales, evidence states, limitations, and sign-off controls.

The HTML is the required report. The JSON trace is required evidence, not an optional developer artifact. Word is optional.

Report contents

The report must include:

• reviewed query and query hash;
• run ID, source mode, generated time, and schema version;
• P002-reported total, retrieved count, deduplicated count, scored count, selected count, and final percentage;
• candidate cap and truncation state;
• scoring model, version, weights, and overrides;
• family and cutoff conventions;
• top five exact-returned inventor names and counts;
• selected patent table with all required fields;
• one evidence-bounded rationale per selected patent;
• endpoint/connector errors and selected-record data gaps;
• legal-event interpretation boundary;
• model limitations and required human review; and
• reviewer sign-off fields in Word output.

Required selected-patent fields

For each selected patent preserve:

Do not describe P041 simple legal status as proof of enforceability. Do not use title, abstract, drawing, family size, citation count, or AI summary as a proxy for claim scope.

Default scoring standard

Read references/screening-standard.md before executing or modifying the model. The default 100 points are:

Scores are candidate-universe relative. They are not calibrated estimates of currency, probability, commercial importance, validity, or litigation risk.

Numeric evidence

For at least ten candidates, calculate the empirical percentile using available numeric observations only:

percentile(value) = count(available values <= value) / count(available values)
component_score = percentile(value) * 30

For fewer than ten candidates:

• all available values zero: score zero;
• all non-zero values equal: a non-zero record receives 15;
• mixed available values: use the empirical percentile and label it unstable;
• missing/error/not-run: score zero under the default missing-data policy while preserving the non-zero evidence state.

Always report available and missing counts. A numeric zero returned by an endpoint is different from no returned evidence.

Core inventors

1. Split inventor records on |, semicolon, full-width semicolon, and line breaks.
2. Never split on comma or full-width comma. Patsnap commonly returns LASTNAME, FIRSTNAME|LASTNAME, FIRSTNAME; the comma is inside one name.
3. Normalize whitespace only and count a name once per patent.
4. Rank exact-returned names by candidate patent count descending, then name ascending.
5. Treat the first five as core inventors.
6. Score 20 when a patent contains at least one exact match; otherwise zero.

Do not automatically merge initials, spelling variants, transliterations, maiden names, reordered names, or homonyms. Record a user override and its provenance. Do not use final patent scores to define the inventors who contribute to those scores; that is circular.

Legal-event activity

Qualifying source categories:

• Litigation — P034 patent_litigation_data;
• Reexamination or invalidation — P027 patent_reexam_invalid_data;
• License — P028 patent_license_data;
• Transfer — P029 patent_transfer_data.

Score 20 if at least one verified event record exists in any category. Score zero if all four checks succeeded and returned empty. If any required check is missing, failed, or not run, retain the zero-point policy but state that absence cannot be concluded.

An event is not inherently valuable. Litigation and invalidation may be adverse; a license may be expired or intra-group; a transfer may be a security interest or corporate restructuring. Preserve dates, case/proceeding numbers, parties, country/authority, event type, and source locator when returned.

Selection count

Default:

selected_count = ceil(deduplicated_candidate_count * 0.10)
maximum_count = ceil(deduplicated_candidate_count * 0.15)

Rules:

• zero candidates yields zero selections and a valid no-results report;
• any non-zero candidate universe yields at least one selected record;
• never exceed 15% without a recorded user instruction;
• resolve cutoff ties using deterministic tie-breaks, not by including every tied record; and
• state both the selected count and percentage.

Tie-break order:

1. higher available simple-family forward-citation count;
2. higher available simple-family size;
3. verified legal-event hit;
4. core-inventor hit;
5. more verified event categories;
6. earlier valid application date;
7. publication number ascending;
8. stable internal identifier ascending.

Missing values rank below available values, including factual zero.

Complete eight-stage workflow

The source package contains ten Python files and eight stages. Preserve all of them; do not collapse away checkpoints or evidence.

Stage 0 — Define scope and run controls

• Confirm the reviewed query and contextual scope.
• Select REST or MCP-import source mode.
• Generate one run ID shared by every checkpoint.
• Set a documented maximum record count.
• Confirm selection ratio and overrides.
• Never place a credential in query text, arguments, logs, outputs, or reports.

Stage 1 — Retrieve P002 candidates

Use P002 /search/patent/query-search-patent/v2.

• Send the exact approved query_text.
• Page with bounded limit and offset.
• Retain reported total and per-page request evidence.
• Detect repeated page signatures and stop with an error.
• Record truncation when the agreed maximum is reached.
• Normalize identifiers, title, assignee, inventor, dates, and authority.
• Deduplicate by patent_id, then publication number fallback.
• Preserve duplicate decisions.
• Output cand_raw.json.

An empty result is a valid state only after a successful call. A request failure is not a no-results conclusion.

Stage 2 — Enrich every candidate with numeric evidence

For all deduplicated candidates:

• P014 /basic-patent-data/patent-family for simple-family members;
• P015 /basic-patent-data/forward-citation/v3 for cited_by_simple_family and available detail fields.

Batch within documented endpoint limits. Preserve available, empty, missing, error, or not_run, along with request evidence and errors. Output enrich_num.json.

Stage 3 — Enrich every candidate with legal events

For every candidate retrieve:

• P034 /high-value-data/litigation;
• P027 /advanced-patent-data/re-examination-and-invalidation;
• P028 /advanced-patent-data/license-data;
• P029 /advanced-patent-data/transfer-data.

Retain complete returned event arrays, normalized English category, state, count, request evidence, and error. Output enrich_legal.json.

Stage 4 — Calculate and rank

• Compute top-five exact-name inventors or apply a reviewed override.
• Build numeric vectors from available values only.
• Apply the documented numeric fallbacks.
• Calculate all four components and total.
• Record missing-policy points separately from raw evidence state.
• Apply all deterministic tie-breaks.
• Select the approved 10–15%.
• Output scored.json with all candidates, not only selections.

Stage 5 — Enrich selected records for display

For selected patents only:

• P021 /basic-patent-data/abstract-image;
• P025 /high-value-data/tech-problem-and-benefit-summary with lang=en;
• P041 /basic-patent-data/simple-legal-status.

P021 links may expire. Store their state and text alternative; download only for an explicitly requested Word report, allow HTTP(S) only, reject redirects, cap bytes, require an image content type, and handle expiration safely. Output enrich_display.json.

Stage 6 — Assemble records and trace

Join scored.json, enrich_display.json, and cand_raw.json by run ID and patent identifier.

• Reject mismatched run IDs.
• Generate evidence-bounded English rationales.
• Preserve all component scores and states.
• Retain event-level evidence and errors.
• Do not build an undocumented China or global product deep link.
• Render a publication hyperlink only when a verified stable global URL is supplied.
• Output final_records.json and high_value_patent_screening_data.json.

Stage 7 — Generate required HTML

Use scripts/hv_7_html_a.py.

• Escape every dynamic value.
• Permit only absolute HTTP(S) URLs.
• Use rel="noopener noreferrer" for external links.
• Include no scripts or event handlers.
• Use semantic headings, tables, captions, text states, local table overflow, responsive breakpoints, reduced-motion support, and Letter landscape print rules.
• Avoid gradients, glow, decorative badges, emoji, and color-only meaning.
• Include all methodology, gaps, limitations, provenance, and reviewer gates.

Stage 8 — Generate optional Word

Use scripts/hv_8_word.py only when requested.

• Keep selection, scores, rationales, evidence states, and limitations aligned with HTML/JSON.
• Use US-Letter landscape, Arial, restrained navy/teal/charcoal, real styles, repeating table headers, page numbers, fixed margins, and text labels.
• Use safe HTTP(S) hyperlinks only.
• Keep image download off by default.
• Include sign-off controls and metadata without personal paths.

REST authentication and call policy

Global base URL:

https://connect.patsnap.com

Authentication:

Authorization: Bearer <private-api-key>

Use PATSNAP_API_KEY or an explicitly configured PATSNAP_API_KEY_FILE. Do not accept a default working-directory key file. Require HTTPS, reject redirects, bound connect/read timeouts, retry only transient HTTP states and network exceptions, honor bounded Retry-After, and return structured safe errors. Never persist credentials or response bodies in exceptions.

The source filenames and P-number labels are retained for topology and workflow fidelity. Verify current global endpoint contracts before a live run.

Verified Patsnap MCP mapping

MCP is optional and available only in an MCP-capable host. The reference Python pipeline executes REST; it must never claim it directly called MCP.

For MCP-import evidence, record connector key, tool name, normalized request, retrieval time, record identifiers, and source response locator. Do not mix REST and MCP-import provenance within one retrieval record. Normalize imported data to the same checkpoint states and retain raw evidence outside the report where the execution environment permits.

Checkpoint contract

Every checkpoint must contain:

• schema_version;
• stage;
• run_id;
• generated_at with timezone;
• source_mode;
• query hash when applicable;
• upstream checkpoint SHA-256 when applicable;
• candidate or selected count;
• structured records;
• request/connector evidence; and
• structured errors.

Consumers must reject incompatible schema versions, missing required fields, and mismatched run IDs. Keep the complete chain with the final report.

Failure handling

Quality gates

Before delivery verify:

• exact source file topology is preserved;
• all source stages, endpoints, metrics, fields, checkpoints, outputs, and optional Word behavior remain represented;
• P002 totals reconcile with retrieved, deduplicated, scored, and selected counts;
• selected count is within the approved 10–15% rule;
• available zeros are distinguishable from missing/error/not-run;
• every selected patent traces through all checkpoints;
• inventor commas are not fragmented;
• no automatic cross-language identity merge occurs;
• all four legal-event categories retain event-level evidence;
• event activity is not presented as inherently positive;
• citation and family limitations are visible;
• technical summaries are English and clearly sourced;
• publication links are verified global HTTP(S) or plain text;
• HTML has no unescaped dynamic markup, script, handler, unsafe URL, or color-only meaning;
• Word contains no personal metadata, local link, floating decorative object, or China-only content;
• credentials and private paths are absent;
• all JSON and YAML parse;
• all Python files pass AST and CLI checks;
• no __pycache__ or .pyc is distributed; and
• a human reviewer approves the query, evidence gaps, event meaning, scoring interpretation, selected narratives, and intended use.

Reference implementation

Read:

• references/screening-standard.md for model details, states, schema, and rationale wording;
• scripts/README.md for secure setup, stage execution, MCP boundaries, and artifact review;
• scripts/hv_common.py for global REST, retry, provenance, and checkpoint helpers;
• scripts/hv_1_fetch.py through scripts/hv_8_word.py for the complete source stage topology; and
• scripts/run_all.py for end-to-end orchestration.