Skill: wwt1995/solution-case-finder (version 1.0.2)

--- name: solution-case-finder description: Help automotive, small-appliance, semiconductor, and mechanical-manufacturing R&D teams solve engineering bottlenecks by finding reference cases for similar technical problems. Compare how others handled tradeoffs, solution patterns, and patent-derived innovation cases. version: 1.0.2 trigger: "solution case finder|reference case|similar engineering problem|technical tradeoff|how others solved|how did others solve|patent case|patent cases|R&D problem|engineering problem|engineering solution|similar solution|solution pattern|solution case|innovation case|cross-industry solution|technical problem|TRIZ|technical contradiction|inventive principle|scientific effect" tools: - mcp - http metadata: openclaw: primaryEnv: TRIZ_CASE_QUERY_MCP_ENDPOINT envVars: - name: TRIZ_CASE_QUERY_MCP_ENDPOINT required: false description: MCP gateway endpoint for triz-case-query. Default: https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap. - name: TRIZ_CASE_QUERY_APP_ID required: false description: Optional APP_ID query value when the gateway endpoint is provided without query parameters. - name: TRIZ_CASE_QUERY_LEAD_URL required: false description: Optional landing page or trial request URL shown only when the user asks for full exports, enterprise access, or follow-up. --- # Solution Case Finder ## Public Positioning Lead with the user's concrete problem: they are blocked by an engineering bottleneck and want practical reference cases before choosing a design direction. Public listing copy should put the value first: "Help automotive, small-appliance, semiconductor, and mechanical-manufacturing R&D teams solve engineering bottlenecks by finding reference cases for similar technical problems. Compare how others handled tradeoffs, solution patterns, and patent-derived innovation cases." Do not position the skill as a TRIZ teaching tool. TRIZ labels are an internal analysis advantage, not the primary acquisition message. In user-facing answers, prefer terms such as reference cases, engineering tradeoffs, solution patterns, patent-derived cases, and cross-industry examples. ## Language Policy This ClawHub skill is designed for English input and English output. Always answer in English. If the user asks in another language, internally translate the request into English and continue in English. If the technical meaning is ambiguous after translation, ask a concise English clarification question. Do not include non-English examples, headings, CTAs, or fallback instructions in user-facing responses. If MCP case fields contain non-English source text, translate or summarize those fields into English before showing them to the user. Do not expose mixed-language raw source fragments in the default answer. ## When to Use Use this skill when a researcher, engineer, product developer, patent analyst, or innovation lead directly enters a technical problem and asks for reference cases showing how similar problems have been solved before. The skill is mainly intended for R&D users in four industry domains: automotive, small appliances, semiconductors, and mechanical manufacturing. The user can call the skill and input their own problem directly; do not require them to use a fixed prompt template. The underlying case library is exposed through the MCP source `triz-case-query` and contains structured patent-derived solution cases. ## Input Examples Users can enter their own technical problem directly. They may use a plain question or a structured technical-contradiction statement. Plain question examples: - How can an EV battery pack reduce thermal runaway propagation between cells and modules without adding too much weight or cooling complexity? - How can a semiconductor package improve heat dissipation while controlling warpage and keeping the package thin? Technical-contradiction input example: ```text If a conventional indoor fan is mounted inside the enclosure, then the structure is simple and easy to manufacture, but the conditioned air cannot be discharged over a long distance. ``` Typical user intents: - Find historical solution cases for a technical tradeoff. - Map a practical engineering problem to reusable solution patterns. - Compare how different industries solved similar constraints. - Get R&D inspiration from structured solution cases without reading raw patent documents. This skill provides R&D inspiration and structured case retrieval. It must not present results as legal advice, freedom-to-operate analysis, infringement judgment, patentability opinion, or a substitute for professional IP counsel. ## Required Capability Use the configured MCP server named `triz-case-query`. Default endpoint: `https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap` The source exposes one MCP tool: - Tool name: `case_query` - Required argument: `user_question` - Input shape: `{ "user_question": "<technical problem description>" }` - Return shape: JSON text containing `status`, `error_code`, `data.total`, and `data.cases[]` Each case may include: - `problem_summary` - `effect_summary` - `innovation_summary` - `triz_technical_contradiction` - `triz_svop` - `triz_scientific_effects` - `relevance_score` - Internal traceability fields such as `case_id`, which should not be shown by default. For connection details, read `references/mcp-integration.md`. If the MCP service is unavailable, use the fallback policy in `references/lead-and-fallback.md`. Do not fabricate case IDs, patent identifiers, case counts, scores, or source evidence. ## Core Workflow 1. Understand the user's R&D problem. - Identify object, function, failure mode, target improvement, constraint, industry, and operating conditions. - If the problem is underspecified, ask at most two concise English clarifying questions before searching. - If enough information exists, proceed without delaying the user. 2. Convert the problem into a case search frame. - Extract the improving parameter and worsening parameter. - Identify the likely technical tradeoff or contradiction. - Identify candidate solution pattern labels. - Keep the search frame concise and in English. 3. Query `triz-case-query.case_query`. - Pass a compact English problem statement as `user_question`. - Include useful context when the user gives it, such as industry, object, constraint, and target metric. - Sort returned cases by `relevance_score` in descending order before presenting them when scores are available. - If some scores are missing, keep unscored cases after scored cases while preserving returned order among unscored cases. - If all returned cases have `relevance_score` missing or null, do not fabricate scores and do not show per-case score lines. State once that MCP did not provide numeric scores, then present all returned cases in MCP order. - Prefer cases with clear problem-solution mapping, explicit tradeoffs, reusable solution patterns, SVOP, and scientific effects. 4. Select and synthesize results. - Group cases by solution pattern, not only by industry. - Highlight repeated inventive principles. - Explain why each case is relevant to the user's contradiction. - Extract transferable design ideas and experimental next steps. - Do not show internal `rank` values or `case_id` in the default user-facing answer. Use them only internally for traceability or when the user explicitly asks for source identifiers. - Present every case returned by the MCP service. Do not truncate to only the top cases by default. - If the returned case count is too large for a single response, continue in batches and clearly show total returned, cases shown in the current batch, and remaining cases. 5. Return a compact, source-grounded answer. - Use the structure in `references/output-format.md`. - Include the six important case fields when available: `problem_summary`, `effect_summary`, `innovation_summary`, `triz_technical_contradiction`, `triz_svop`, and `triz_scientific_effects`. - Include `relevance_score` only when the MCP provides a numeric value. Do not show `Relevance score: Not provided by MCP`. - Clearly label uncertainty when evidence is incomplete. - End with one practical next action, such as refining constraints or asking for a deeper case comparison. ## Query Rules For detailed query expansion, ranking, and cross-industry analogy rules, read `references/triz-query-rules.md` when the user asks a concrete technical question or when MCP results are noisy. For user entry points, no-MCP fallback, and lead generation CTA rules, read `references/lead-and-fallback.md`. For expected answer structure, read `references/output-format.md`. For high-converting English prompt examples and demo scenarios, read `references/example-questions.md` when preparing onboarding text, listing copy, demos, or test prompts. ## Response Style Answer in clear, professional English. Keep the tone practical and useful for R&D teams. Be specific: - Say "The transferable idea is..." instead of giving generic inspiration. - Say "The relevant tradeoff is..." before listing solution patterns. - Say "This should be validated by..." for assumptions and experiments. Do not overclaim: - Do not say a solution is novel, non-infringing, or legally safe. - Do not imply the retrieved case teaches every implementation detail unless the MCP evidence supports it. - Do not hide that results come from a bounded patent-derived case dataset. ## Failure Handling If no strong case is found: 1. Explain which search frame was attempted. 2. Provide the closest adjacent patterns. 3. Suggest how the user can reframe the problem with more constraints. If the user asks for raw full-text patent exports, confidential datasets, bulk scraping, or private credentials, refuse that part and offer a summarized, traceable case analysis instead. If the user asks where to use this skill, explain that ClawHub is the discovery and installation surface. The actual question is entered directly in the user's ClawHub-compatible Agent chat after installing this skill and configuring the `triz-case-query` MCP endpoint.

path: references/example-questions.md
content: # Example Questions

Use these for demos, listing copy, tests, and onboarding.

## Small Appliances

- How can others reduce fan noise without sacrificing airflow?
- How have similar products improved heating speed without causing local overheating?
- How can a handheld vacuum reduce weight while maintaining structural strength?

## Automotive

- How have others improved battery pack heat dissipation without increasing volume and pipe complexity?
- How can an automotive seat reduce weight while maintaining crash strength?
- What cross-industry cases are relevant to reducing HVAC noise while maintaining airflow?

## Semiconductor

- How have others improved semiconductor package heat dissipation while controlling warpage?
- How can wafer cleaning improve particle removal while reducing surface damage?
- How have precision positioning systems improved accuracy without reducing throughput?

## Mechanical Manufacturing

- How can a fixture achieve high positioning accuracy and fast changeover at the same time?
- How have others increased machining efficiency while reducing tool wear?
- How can an automated production line improve flexibility without adding too much mechanical complexity?

## Cross-Industry

- Can automotive thermal management cases be transferred to small appliances?
- Can precision positioning cases from semiconductor equipment be applied to mechanical fixtures?
- Can small-appliance noise reduction patterns be transferred to automotive air duct design?


path: references/lead-and-fallback.md
content: # User Journey, Fallback, and Lead Capture

## User Entry Point

ClawHub is the discovery and installation surface. The user does not ask questions on the ClawHub listing page itself.

Expected path:

1. The user finds `Solution Case Finder` on ClawHub.
2. The user installs the skill into an OpenClaw or ClawHub-compatible Agent environment.
3. The environment has MCP server `triz-case-query` configured.
4. The user directly calls the skill and enters their own technical problem in the Agent chat.
5. This skill triggers and calls `case_query`.
6. The answer summarizes relevant reference cases, core case fields, transferable patterns, and next experiments.

Internal demo and test examples. These are not required user wording:

- How can others reduce fan noise without sacrificing airflow?
- How have others improved semiconductor package heat dissipation while controlling warpage?
- How can a fixture achieve high positioning accuracy and fast changeover at the same time?

## No-MCP Fallback

If MCP is not configured, unreachable, or returns an authentication or protocol error:

1. Do not invent cases.
2. Explain that case retrieval requires `triz-case-query`.
3. Still provide a lightweight TRIZ framing:
   - likely contradiction
   - candidate inventive principles
   - recommended refined query
4. Ask the user to configure the MCP endpoint or provide access.

Fallback response pattern:

```text
I can frame the problem for TRIZ-style retrieval, but I am not connected to the triz-case-query MCP server, so I cannot return real cases yet.

Suggested retrieval question:
...

Required MCP configuration:
/mcp add triz-case-query https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap
```

## Lead Capture CTA

Do not add a sales pitch to every answer.

Use a CTA only when:

- the user asks for complete case lists, exports, or batch analysis
- the user asks for enterprise deployment, API access, private data, or team access
- the answer has already delivered useful value from retrieved cases

CTA style:

```text
If you need to export the full result set, filter cases by industry or inventive principle, or integrate this workflow into an enterprise R&D process, you can request full access.
```

If `TRIZ_CASE_QUERY_LEAD_URL` is configured, include it. If not configured, say "Contact the platform administrator to request full access" rather than inventing a URL.

## Pre-Publish Review Gates

Before publishing to ClawHub, confirm:

- The `triz-case-query` endpoint is approved for public ClawHub users.
- `APP_ID=Patsnap` can be used publicly, or replace it with a production app id or authentication method.
- The MCP response does not leak raw patent full text or confidential customer data.
- The listing clearly says the skill provides R&D inspiration, not legal opinions.
- The demo answer shows relevance score handling plus the six important case fields, and does not show internal rank or source identifiers by default.
- The ClawHub publish step is run only after owner review.


path: references/mcp-integration.md
content: # MCP Integration

## Confirmed Source

- Resource Hub source URL: `https://aws-us-prod-s-data-platform-resource-hub-internet.patsnap.info/sources/f8cf1ac6-3b05-4151-b78b-6e2850257e3e`
- MCP source name: `triz-case-query`
- External endpoint pattern observed from the Resource Hub frontend: `https://ai-fabric.patsnap.com/mcp/{source_name}?APP_ID=Patsnap`
- Effective endpoint for this skill: `https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap`

The Resource Hub page requires console login for private source details. The public endpoint was verified through MCP protocol calls.

## Protocol

Use JSON-RPC over HTTP with SSE response support.

Required headers:

```http
Content-Type: application/json
Accept: application/json, text/event-stream
```

Useful verification calls:

```json
{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}
```

```json
{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "case_query",
    "arguments": {
      "user_question": "How can others reduce fan noise without sacrificing airflow in a compact appliance fan design?"
    }
  }
}
```

## Tool Schema

Tool name: `case_query`

Translated tool description:

Given a user's technical problem description, the tool searches a TRIZ-labeled solution case library and returns a ranked list of relevant cases. Each case may include a problem summary, effect summary, innovation summary, TRIZ technical contradiction, SVOP analysis, and scientific effect data.

Input schema:

```json
{
  "type": "object",
  "required": ["user_question"],
  "properties": {
    "user_question": {
      "type": "string",
      "title": "User Question",
      "description": "Technical problem description provided by the user"
    }
  }
}
```

Observed response fields:

- `status`
- `error_code`
- `data.total`
- `data.cases[].case_id`
- `data.cases[].problem_summary`
- `data.cases[].effect_summary`
- `data.cases[].innovation_summary`
- `data.cases[].triz_technical_contradiction`
- `data.cases[].triz_svop`
- `data.cases[].triz_scientific_effects`
- `data.cases[].relevance_score`

## Host Configuration

For OpenClaw or Claude Code style clients, add the MCP server by endpoint:

```bash
/mcp add triz-case-query https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap
```

For clients that need a config object:

```json
{
  "mcpServers": {
    "triz-case-query": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/inspector",
        "https://ai-fabric.patsnap.com/mcp/triz-case-query?APP_ID=Patsnap"
      ]
    }
  }
}
```

## Production Note

The Resource Hub frontend marks `APP_ID=Patsnap` as a test value that may be removed. Before public ClawHub release, confirm whether to keep this APP_ID or replace it with a production app id or gateway authentication method.


path: references/output-format.md
content: # Output Format

Use this structure for concrete R&D problem answers.

All user-facing content must be English. If MCP fields contain non-English raw text, translate or summarize that content into English before presenting it.

## 1. Problem Restatement

Restate the problem as an engineering contradiction:

- Improve:
- Worsening side effect:
- Key constraints:
- Application context:

## 2. TRIZ Frame

List:

- Technical contradiction:
- Candidate inventive principles:
- Search keywords:

Keep this section short. The user wants useful cases, not a TRIZ lecture.

## 3. Similar Solution Cases

Sort cases by `relevance_score` in descending order before presenting them. If a case has no score, place it after scored cases and keep its original MCP order among other unscored cases.

If all returned cases have `relevance_score` missing or null, do not fabricate scores. Add one short note: "The MCP did not provide numeric relevance scores for this query, so cases are presented in the returned order." Do not show a `Relevance score` line or column when scores are missing.

Present every case returned by the MCP service. Do not default to a top-3, top-5, or top-10 subset. If the returned case count is too large for a single response, continue in batches and clearly show:

- total cases returned
- cases shown in the current batch
- remaining cases

Do not show `rank` or `case_id` in the default user-facing answer. These are internal traceability fields and are not useful for most R&D users. Show source identifiers only if the user explicitly asks for them.

Use a compact table only if it remains readable. For many cases or long fields, present each case as a short structured block. Include the six important MCP fields, and include `relevance_score` only when the MCP provides a numeric value.

Recommended fields:

- problem_summary
- effect_summary
- innovation_summary
- triz_technical_contradiction
- triz_svop
- triz_scientific_effects

If numeric `relevance_score` values are present, include `relevance_score` before `problem_summary`.

## 4. Transferable Solution Patterns

Summarize 2 to 4 reusable patterns, such as:

- Segmentation and modularization
- Preliminary action
- Dynamic structure or dynamic control
- Intermediary
- Local quality
- Parameter changes
- Composite materials or functional gradients

Explain how each pattern could transfer to the user's product, process, or system.

## 5. R&D Next Steps

Give 2 to 3 concrete next steps:

- one design direction
- one validation experiment
- one data point or constraint to collect next

## Legal and Confidence Note

When appropriate, add:

"These results are R&D inspiration based on a structured patent-derived case dataset. They are not infringement opinions, freedom-to-operate analysis, or patentability advice."


path: references/triz-query-rules.md
content: # TRIZ Query Rules

## Problem Extraction

Extract these fields before querying:

- product or component
- function to improve
- failure mode or pain point
- measurable target
- worsening side effect
- industry domain
- material, structure, process, or control constraints
- operating environment

If the user gives only a broad problem, generate a best-effort query and ask one clarifying question after returning initial patterns.

## MCP Query Input

The `case_query` tool only accepts one required field, `user_question`.

Build `user_question` as a compact English natural-language description. Include:

- user's original question
- product or component
- improvement target
- worsening constraint
- industry if known
- measurable constraints if known

Example:

```json
{
  "user_question": "A compact appliance fan should reduce noise without sacrificing airflow or increasing product volume. Search for similar TRIZ solution cases, especially airflow path design, fan control, and structural noise reduction."
}
```

Do not send complex filters unless the MCP schema later exposes them.

## Query Expansion

Before calling MCP, mentally expand the question with three layers, but keep the actual tool input concise:

1. Direct technical terms from the user.
2. TRIZ contradiction terms:
   - improve speed vs accuracy
   - improve strength vs weight
   - improve heat dissipation vs volume
   - improve sealing vs assembly convenience
   - improve noise reduction vs airflow
   - improve yield vs process complexity
3. Inventive principle labels:
   - segmentation
   - taking out
   - local quality
   - asymmetry
   - merging
   - universality
   - nested doll
   - counterweight
   - preliminary action
   - prior cushioning
   - equipotentiality
   - inversion
   - spheroidality
   - dynamics
   - partial or excessive action
   - another dimension
   - mechanical vibration
   - periodic action
   - continuity of useful action
   - skipping
   - blessing in disguise
   - feedback
   - intermediary
   - self-service
   - copying
   - cheap short-living objects
   - mechanics substitution
   - pneumatic or hydraulic construction
   - flexible shells and thin films
   - porous materials
   - color changes
   - homogeneity
   - discarding and recovering
   - parameter changes
   - phase transitions
   - thermal expansion
   - strong oxidants
   - inert atmosphere
   - composite materials

## Industry Priority

Default search order:

1. User-specified industry.
2. Adjacent industries with similar physics or process constraints.
3. Cross-industry analogy among small appliances, automotive, semiconductor, and mechanical manufacturing.

Examples:

- Noise vs airflow: small appliances, automotive HVAC, rotating machinery.
- Heat dissipation vs compactness: semiconductor packaging, automotive thermal management, appliances.
- Accuracy vs speed: semiconductor process tools, mechanical fixtures, automotive assembly.
- Strength vs weight: automotive structures, mechanical manufacturing, appliance housings.

## Ranking

When `relevance_score` is provided, sort cases by score in descending order. When all scores are missing or null, preserve the MCP returned order. Present all returned cases by default, then summarize recurring patterns after the case list.

- clear problem-solution mapping
- explicit TRIZ principle labels
- source traceability for internal use
- same physical contradiction
- transferable mechanism, not just similar keywords
- recent or widely cited cases when available

If some cases only share surface words but solve a different engineering tradeoff, keep them in the full returned list but clearly mark them as weaker analogies rather than removing them.

## Synthesis

Do not simply list cases. Cluster cases into solution patterns and explain the transfer logic:

- Same contradiction, different industry.
- Same inventive principle, different structural implementation.
- Same structural pattern, different material or process condition.

Always distinguish direct applicability from analogy.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)