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create-patent-search-report-ip

该 Skill 位于专利景观分析流程第 4/4 阶段,复用检索、统计、分类和人工标注工件,核验范围与计数,综合技术演进、分支价值信号和专利包证据,输出离线自包含的 report.html 及记录来源、证据与限制的 report_manifest.json。

yuanzhian-patsnap
yuanzhian-patsnap
热度 13.72
最近更新 2026-08-13 16:10:18
分类:数据依赖:读写文件 / 代码执行 / MCP 服务应用场景:报告撰写 / 研究 / 数据处理 / 市场分析 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add create-patent-search-report-ip
Metadata
copyright
Copyright © PatSnap. All rights reserved.
name
create-patent-search-report-ip
description
Create the final evidence-backed patent-landscape insight report from validated search, statistics, taxonomy, patent-package, and human-tagging artifacts. Use at Stage 4/4 of the create-patent-landscape-overview-ip suite to aggregate a large tagged patent pool safely, synthesize technology evolution and branch-level value signals, translate patent-package evidence into bounded user actions, and write report_manifest.json plus one self-contained scientific HTML report.

Create a Patent Search Report

Role in the suite

Act as Stage 4/4, the reporting and synthesis stage of create-patent-landscape-overview-ip.

Upstream stages are:

  1. search-patents-ip — validated scope and candidate records.
  2. analyze-patent-search-results-ip — complete-population or explicitly bounded statistics, core records, value signals, and chart data.
  3. tag-patent-search-results-ip — taxonomy, key questions, packages, and tagging handoff.
  4. Human Stage 3.5 — validated return of tagged_pool.csv when performed.

Turn those artifacts into a decision-readable report. Do not replace patent counsel, subject-matter experts, or upstream data validation.

Questions this stage answers

  • Which findings matter to the stated product, R&D, strategy, or IP decision?
  • Which activity patterns, organizations, branches, and patent groups deserve attention?
  • How does the evidence suggest that technical routes have changed over time?
  • Where do multiple dated patent-value proxies concentrate by branch?
  • What can a user reasonably monitor, read, compare, validate, or refer for review?
  • Which claims remain uncertain because data, tagging, or expert review is incomplete?

Preconditions

Use this stage only when:

  • the user has confirmed report objective and audience;
  • Stage 1 search scope is validated;
  • Stage 2 statistics and provenance are available;
  • Stage 3 taxonomy/package artifacts or a sufficiently rich human-tagged pool are available; and
  • the output environment permits creation of report_manifest.json and report.html.

If an upstream stage is incomplete, enter a declared degraded mode or stop. Do not invent the missing artifact.

Authoritative artifact contract

The suite has no packaged ARCHITECTURE.md. Use this embedded contract.

Stage 1 inputs

Artifact Required content
search_config.json Scope, queries, exclusions, date/language/jurisdiction fields, unit, query version, connector provenance
candidate_pool.csv Candidate records with stable IDs and retrieval/screening state
core_recall.csv Known-relevant/near-miss controls and recall-review evidence

Stage 2 inputs

Artifact Required content
panorama_stats.json Trends, organizations, jurisdictions, status signals, technology distributions, and competitor profiles supported by the population boundary
patent_index.core.json or equivalent source-authorized core format Reviewed and tiered representative patents, branch IDs, evidence provenance
value_signals.json Candidate-level dated proxy signals and verification state
chart_data.json Chart-ready aggregates with measure, unit, date basis, cutoff, scope, and limitations
panorama_stats_report.html Stage 2 statistical snapshot; never substitute it for this insight report

Stage 3 inputs

Artifact Required content
tech_breakdown.json Versioned technology taxonomy and four-column decomposition
key_questions.json Decision-relevant questions, branch/node seeds, rationale, and review status
patent_packages.csv Evidence-backed patent groups, selection rubric, rationale, and review status
tagging_demo_sample.csv Reviewed example tags and boundary cases
to_be_tagged.csv Human-tagging input and schema/version metadata

Human Stage 3.5 input

Artifact Required content
tagged_pool.csv Returned complete or explicitly bounded pool, validated taxonomy tags, technical fields, family IDs, assignee, dates, status/signals, schema/taxonomy version, row count, encoding, and reconciliation data

Stage 4 outputs

Artifact Content
report_manifest.json Mode, scope, input versions/checksums, section-to-source map, evidence register, derived-field rules, limitations, output inventory, and QA state
report.html One offline, self-contained, accessible scientific/executive insight report

Create report_manifest.json only at Stage 4. Do not expect a Stage 2 manifest with the same name. Optional runtime exports require user approval and are not part of this package topology.

Verify inputs before synthesis

For every available artifact:

  1. confirm exact path and readable format;
  2. record file size, row/object count, checksum when supplied or practical;
  3. validate schema and version;
  4. reconcile project, query, taxonomy, family, and data-cutoff identifiers;
  5. reconcile candidate, deduplicated, tagged, and reported counts;
  6. identify missing columns, null patterns, and conflicting values;
  7. preserve the previous accepted version for rollback; and
  8. record validation status in the manifest.

Stop if material inputs belong to different scopes or versions and cannot be reconciled.

Reporting modes

Mode A — validated tagged-pool driven

Use when tagged_pool.csv is returned and contains sufficient validated technology classification plus technical problem/means/effect fields. Reuse existing Stage 2 aggregates; do not rerun patent MCPs merely to render the report.

Inputs:

  • tagged_pool.csv as the classification and technical-evidence body;
  • panorama_stats.json, value_signals.json, patent_index.core.*, and chart_data.json as validated Stage 2 evidence; and
  • Stage 3 artifacts when available.

If Stage 3 questions/packages are absent, derive provisional route and package views from the tagged pool under the rules below. Label them automated_derivation, not human-rubric output.

Mode B — full Stage 3 contract

Use when tech_breakdown.json, key_questions.json, and patent_packages.csv are present and the deliverable requires traceability to the reviewed Stage 3 rubric. Combine them with the tagged pool and Stage 2 evidence.

Degraded mode — statistics and reviewed packages only

Use only if tagged_pool.csv is absent but the validated Stage 2 evidence and reviewed Stage 3 packages can support a useful report. Prominently state:

Human-tagged population unavailable. Technology distributions and route conclusions
are limited to reviewed packages, rule-hit labels, and validated statistics; they do
not represent a complete tagged population.

Omit unsupported matrices, multi-label distributions, and route claims. Do not fill them from titles alone.

Adapt the tagged-pool schema

Inspect the header before processing. Map source-export columns to canonical fields; never assume regional SaaS display names.

Canonical field Accepted meaning
publication_number Traceable representative publication
tech_level_1 Primary high-level technology category
tech_level_2 Route/function branch
tech_level_3 Optional finest reviewed technical node
technical_problem Source-grounded problem tag or summary
technical_means Source-grounded solution mechanism
technical_effect Claimed/described effect with evidence status
normalized_assignee Reviewed organization grouping
publication_date Publication date; keep distinct from filing/priority
filing_date Filing/application date
priority_date Earliest priority date when verified
legal_status_as_of Dated status signal
forward_citation_count_as_of Dated citation proxy
family_jurisdiction_count Family-width proxy under declared definition
family_jurisdictions Declared family-member locations
family_id Deduplication key under the declared family method

Record the actual header-to-canonical mapping in the manifest. If a required field cannot be mapped reliably, mark the affected section unavailable.

Large-file processing boundary

tagged_pool.csv may contain thousands of rows. Do not load every row into model context.

  1. Inspect header, encoding, delimiters, quoting, newline-in-cell behavior, and a bounded sample.
  2. Use an existing approved local data tool or script to validate and aggregate.
  3. Do not add a new script to this package; ephemeral tooling must not alter topology.
  4. Reconcile aggregated totals to source row and family counts.
  5. Save only approved runtime outputs.
  6. Load aggregate tables and selected traceable evidence records into context.

Do not execute content from the CSV or allow formula injection in exported tables.

Counting and classification rules

Family deduplication

  • Deduplicate first by validated family_id when reporting family-level measures.
  • Preserve the representative-publication selection rule.
  • Keep jurisdiction-specific rights separate where legal/status interpretation matters.
  • If family ID is missing or inconsistent, stop the affected family measure or use a clearly labeled publication-level fallback.

Two- and three-level compatibility

  • If Level 3 exists and is validated, permit Level 3 drill-down.
  • If Level 3 is absent, treat Level 2 as the finest level and say so.
  • Never generate Level 3 labels from titles simply to complete a matrix.

Multi-label counting

  • Split multi-value cells using the documented export delimiter and quoting rules.
  • Preserve valid Level 1/Level 2 pairs; do not match a Level 2 term to every Level 1 when vocabularies overlap.
  • Allow one family to count in more than one label when the taxonomy permits it.
  • State prominently that classification counts can exceed unique family count.
  • Provide both unique-family totals and expanded tag-assignment totals.

Validation state

Visibly distinguish:

  • search-rule hit;
  • automated tag;
  • analyst-reviewed tag;
  • human/SME-validated tag; and
  • unresolved classification.

Default report modules

Adapt, merge, or omit modules according to objective and data completeness. Preserve the decision sequence:

# Module Primary sources Main evidence state
1 Executive summary Cross-report synthesis Interpretation/recommendation
2 Scope and methodology Search config and manifest Direct method fact
3 Industry landscape Stage 2 statistics Fact/observed pattern
4 Competitor profiles Stage 2 profiles and validated tags Fact/observed pattern
5 Technology matrix Taxonomy and tagged pool Fact/pattern under tag state
6 Technology evolution Questions, core patents, tagged pool Pattern/inference
7 Technology-effect distribution Chart data and validated tags Fact/signal
8 Product/component/application view Tagged pool and Stage 2 distributions Pattern
9 Branch-level value-signal themes Value signals and core index Dated proxy/inference
10 Curated patent groups Stage 3 packages and value signals Recommendation
11 Risks and limitations All inputs and validation log Boundary
12 Appendix and data assets Manifest and input inventory Reproducibility

Place technology evolution immediately after the technology matrix. Explain signal themes before user actions and patent groups.

Module 6 — Technology evolution

Evidence chain

Build each route as:

versioned branch/question → time-bounded family evidence → technical problem/means/effect
→ observed change → alternative explanation → bounded route interpretation

Summary hierarchy

Include:

Level Field Content
Section evolution_overview Cross-branch observations: acceleration, continuity, convergence, divergence, or emerging attention, each qualified
Route route_summary One sentence describing the observed earlier/current/recent technical emphasis without inventing continuity
Phase phase_caption Evidence-grounded technical characteristics and organizations for that period

Select route evidence

In Mode B, map key_questions.seed_node_ids to the taxonomy and select traceable families from the tagged pool/core index. In Mode A without key questions:

  1. use validated Level 1 branches as provisional routes;
  2. identify dominant valid Level 1/Level 2 pairs by declared measure;
  3. select representative families that match both paired levels;
  4. segment time according to the dataset and decision—quantiles, technology eras, or explicit periods—not fixed calendar years;
  5. consider technical relevance, evidence depth, date, and diversity;
  6. prevent accidental family reuse when it would distort comparison; and
  7. disclose any algorithmic diversity/organization rotation as a sampling choice, not evidence of actual market entry timing.

Do not require three families or three non-empty phases. Show sparse/empty periods.

Turning points

Use controlled types only when evidence supports them:

  • route branching;
  • notable disclosure;
  • organization entry in the observed dataset;
  • disclosed performance or capability change; and
  • application-context shift.

Each turning_point contains type, note, evidence IDs, date basis, and uncertainty. Generate its note from the selected family’s problem/means/effect evidence. Do not invent a transition between records.

Visualization

Use accessible HTML/CSS/SVG timelines or small multiples. Each route shows date basis, family IDs/publications, organization, validated node, evidence state, and sparse-data qualification. Static text must convey the finding without interaction.

Module 7 — Technology-effect distribution

Build a technical-means × reported-effect matrix from validated upstream chart data or tagged-pool aggregation.

  • Define row, column, cell measure, unit, multi-label policy, tag state, and cutoff.
  • Use family count only after validated family deduplication.
  • Distinguish claimed/described effects from independently demonstrated performance.
  • Represent unavailable cells separately from observed zero.
  • Do not call a combination “insignificant” merely because the dataset has no records.
  • Use an accessible heatmap/table or bubbles with a tabular alternative.

Module 9 — Branch-level value-signal themes

Aggregate candidate-level proxies in value_signals.json by validated branch_id. Possible dimensions include dated citation, family breadth, legal-status, organization concentration, transaction/assertion-event, and portfolio-priority signals.

For each dimension record:

  • definition and source;
  • verified versus recall-proxy state;
  • date/cutoff and jurisdiction coverage;
  • normalization and missing-data treatment;
  • aggregation function and denominator; and
  • sensitivity to outliers or branch size.

Describe results as “higher observed signal concentration under this dataset” or “lower observed signal density.” Do not call the score patent value, moat strength, defensibility, blue ocean, freedom to operate, availability, or market opportunity.

Prefer bars, dot plots, or a signal matrix. Avoid radar charts when dimensions have unlike scales or missing values.

Module 10 — Curated patent groups

Preserve analyst evidence

Retain Stage 3 recommendation_reason, rubric dimensions, evidence IDs, review status, and all limitations in the manifest/evidence layer.

Translate into bounded user actions

For each family add:

Field Meaning
use_case Evidence-supported next action such as read, monitor, compare, technical reference, data validation, or counsel/commercial review
purpose_tag Controlled action category approved for this report
answers_question Link to a validated key question when the mapping exists
package_summary What the group addresses, why it matters, and which records to start with

Do not hard-code the source’s five Chinese action labels. Define an English controlled vocabulary appropriate to the objective. Never translate proxies into “design-around,” “licensing candidate,” “acquire,” “enforce,” or “FTO action” without qualified review.

Mode A provisional package derivation

If patent_packages.csv is absent:

  1. derive candidates by validated finest branch;
  2. rank with disclosed relevance, evidence-depth, family/citation/status proxies;
  3. treat missing proxy data explicitly;
  4. test for age, organization, and family-size bias;
  5. select only supported records rather than a fixed two-to-three quota;
  6. label the group automated_derivation; and
  7. require human review before any transaction, legal, or portfolio action.

When no key_questions mapping exists, leave answers_question unresolved. Do not fabricate a question link.

Two-layer rendering

Main layer:

  • decision-readable action;
  • purpose tag;
  • linked question if verified; and
  • package summary.

Expandable evidence layer:

  • original rubric/reason;
  • family, citation, status, organization, and review signals;
  • evidence IDs and provenance; and
  • limitations/legal boundary.

The report must remain understandable when expandable controls are not used or when printed.

Evidence model

Use:

Level Meaning
L1 Direct, source-backed data or method fact
L2 Observed pattern in the defined dataset
L3 Analytical interpretation with alternatives and uncertainty
L4 Business/R&D/IP workflow recommendation
L5 Legal, transaction, status, or risk signal requiring specialist review

Every material claim maps to one or more evidence entries. A manifest evidence entry contains:

{
  "evidence_id": "E-001",
  "level": "L2",
  "claim": "[bounded observation]",
  "source_file": "[validated upstream artifact]",
  "source_field": "[field or aggregate]",
  "record_ids": ["[traceable IDs]"],
  "counting_method": "[unit, deduplication, multi-label policy]",
  "data_cutoff": "[YYYY-MM-DD]",
  "validation_state": "[verified/proxy/reviewed/unresolved]",
  "limitations": "[material boundary]"
}

Do not include confidential examples in the Skill package.

report_manifest.json contract

Include:

  • report ID, version, generated date, objective, audience, and mode;
  • scope, jurisdictions, date basis, unit, family definition, and data cutoff;
  • every input path, artifact version, checksum/size/count, validation result;
  • header/column mappings and transformations;
  • section order and section-to-source/evidence mapping;
  • evolution overview, routes, summaries, phases, and turning points;
  • branch signal definitions and aggregations;
  • package summaries, bounded use cases, purpose tags, question links, original reasons;
  • evidence register;
  • degraded/automated/proxy flags;
  • limitations and unresolved items;
  • output paths and QA results; and
  • no secret, API key, raw confidential payload, or absolute user path.

Write atomically when possible. Validate JSON before handoff.

report.html design contract

Information architecture

  • Start with title, decision objective, mode, scope, date basis, family unit, cutoff, sources, and limitations.
  • Make executive findings evidence-linked and action-bounded.
  • Place each visualization next to its claim and qualification.
  • Preserve the default module sequence unless an approved audience need changes it.
  • End with reproducibility assets and legal/data boundaries.

Scientific/executive visual system

  • Use a white/neutral canvas, dark navy/slate hierarchy, restrained teal data accent, amber qualifications, and red only for real escalation.
  • Use system fonts; do not rely on regional or remote fonts.
  • Prefer whitespace, rules, and typography over nested cards.
  • Use flat 2D bars, lines, heatmaps/tables, timelines, and evidence cards.
  • Avoid decorative hero sections, gradients, stock imagery, 3D charts, visual drama, and vendor-interface imitation.
  • Pair color with labels or symbols and maintain accessible contrast.

Technical safety

  • Deliver one HTML file with inline CSS and pre-aggregated data.
  • Prefer static HTML/CSS/SVG; allow minimal inline JavaScript only as progressive enhancement with a complete non-script fallback.
  • Use no external CDN, D3, font, image, iframe, tracker, or network dependency.
  • Escape all user and retrieved content.
  • Permit only validated safe URLs and add rel="noopener noreferrer" to new-tab links.
  • Do not execute or interpolate raw CSV/JSON content as code.
  • Prevent spreadsheet-formula and HTML/script injection in displayed/exported values.

Accessibility and print

  • Use semantic landmarks, ordered heading levels, table headers/captions, visible focus, keyboard-safe controls, and text equivalents for charts.
  • Keep wide tables horizontally scrollable and long identifiers break-safe.
  • Respect reduced motion and avoid animation needed for meaning.
  • Ensure collapsed evidence is visible or summarized in print.
  • Verify desktop, narrow viewport, grayscale, and PDF/print layouts.

Chart captions

Every quantitative view states:

  • question and bounded takeaway;
  • measure and denominator;
  • date field and period;
  • unit/family definition;
  • scope and cutoff;
  • multi-label duplicate-count policy;
  • validation/proxy state; and
  • material limitation.

Show unavailable data rather than a fake or zero-valued chart.

MCP boundary

Stage 4 normally reuses validated upstream artifacts. Do not rerun MCPs merely to recreate existing statistics.

If an approved material evidence gap requires retrieval, use only the installed live schema of these verified global connectors:

Record why the gap could not be resolved from upstream artifacts and how new evidence was reconciled. Do not use source endpoint aliases as connector names.

Legal and analytical boundaries

Do not provide:

  • formal freedom-to-operate or infringement opinions;
  • patent validity, novelty, or inventive-step opinions;
  • standards-essentiality opinions;
  • legal claim-scope conclusions;
  • patent valuation or transaction recommendations;
  • product-launch or market-adoption certainty; or
  • unsupported business conclusions.

Use language such as “under the defined dataset,” “the patent evidence suggests,” “observed proxy concentration,” and “requires technical, commercial, or legal review.”

Quality gate

Input and mode

  • Every required input exists or the mode declares its absence.
  • Schema, version, count, checksum, scope, taxonomy, family, and cutoff reconcile.
  • Mode A, Mode B, or degraded mode is explicit at the top and in the manifest.
  • No large tagged pool was loaded row-by-row into context.

Data and synthesis

  • Family and multi-label counting rules are applied and disclosed.
  • Population, sample, core set, package, and representative records are distinct.
  • Evolution periods derive from the dataset and contain no fabricated transition.
  • Turning points cite their family and technical evidence.
  • Value themes expose proxy definitions, missing data, aggregation, and limitations.
  • Package actions are bounded and preserve original Stage 3 evidence.

Evidence and law

  • Every material claim maps to evidence IDs.
  • Facts, patterns, interpretations, recommendations, and legal signals are distinct.
  • Status/citation/family/transaction values are dated and source-labeled.
  • No moat, blue-ocean, design-around, licensing, FTO, validity, or value conclusion is inferred from proxies.

Outputs

  • report_manifest.json is valid, complete, and contains no secrets/absolute paths.
  • report.html opens offline and contains all promised sections or explicit omissions.
  • HTML has no missing assets, remote dependencies, unsafe content, broken links, inaccessible controls, blank charts, overlap, clipping, or print loss.
  • Section/evidence counts reported in the handoff match the files.

Handoff

After writing and validating both outputs, return control to create-patent-landscape-overview-ip. Report:

report.html written ([section count] sections, [chart count] charts);
report_manifest.json written ([evidence count] evidence entries).
Mode: [A/B/degraded]. Unresolved: [count and summary].

Do not paste the full HTML into the conversation unless the user asks.

Stop conditions

Stop or degrade when:

  • upstream artifacts are missing, incompatible, or from different scopes;
  • tagged_pool.csv cannot be parsed or reconciled;
  • family or taxonomy identifiers are unreliable for a requested measure;
  • a population claim is unsupported by complete retrieval/aggregation;
  • a required route, value, or package conclusion would need fabricated evidence;
  • confidential data cannot be processed safely;
  • the report cannot be written or validated in the authorized workspace; or
  • a requested conclusion requires expert legal or commercial review.

Return the completed sections, failed validation, affected claims, and exact next step. Do not silently omit a failed section.