# Send Journal Matchmaker to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "journal-matchmaker", "name": "Journal Matchmaker", "source": "tencent", "type": "skill", "category": "内容创作", "sourceUrl": "https://clawhub.ai/AIPOCH-AI/journal-matchmaker", "canonicalUrl": "https://clawhub.ai/AIPOCH-AI/journal-matchmaker", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/journal-matchmaker", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=journal-matchmaker", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "requirements.txt", "SKILL.md", "scripts/main.py", "references/fields.json", "references/journals.json", "references/scoring_weights.json" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "journal-matchmaker", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T00:43:58.932Z", "expiresAt": "2026-05-07T00:43:58.932Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=journal-matchmaker", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=journal-matchmaker", "contentDisposition": "attachment; filename=\"journal-matchmaker-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "journal-matchmaker" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/journal-matchmaker" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/journal-matchmaker", "downloadUrl": "https://openagent3.xyz/downloads/journal-matchmaker", "agentUrl": "https://openagent3.xyz/skills/journal-matchmaker/agent", "manifestUrl": "https://openagent3.xyz/skills/journal-matchmaker/agent.json", "briefUrl": "https://openagent3.xyz/skills/journal-matchmaker/agent.md" } } ``` ## Documentation ### Journal Matchmaker Analyzes academic paper abstracts to recommend optimal journals for submission, considering impact factors, scope alignment, and domain expertise. ### Use Cases Find the best-fit journal for a new manuscript Identify high-impact factor journals in specific research areas Compare journal scopes against paper content Discover domain-specific publication venues ### Usage python scripts/main.py --abstract "Your paper abstract text here" [--field "field_name"] [--min-if 5.0] [--count 5] ### Parameters ParameterTypeRequiredDefaultDescription--abstractstrYes-Paper abstract text to analyze--fieldstrNoAuto-detectResearch field (e.g., "computer_science", "biology")--min-iffloatNo0.0Minimum impact factor threshold--max-iffloatNoNoneMaximum impact factor (optional)--countintNo5Number of recommendations to return--formatstrNotableOutput format: table, json, markdown ### Examples # Basic usage python scripts/main.py --abstract "This paper presents a novel deep learning approach..." # Specify field and minimum impact factor python scripts/main.py --abstract "abstract.txt" --field "ai" --min-if 10.0 --count 10 # Output as JSON for integration python scripts/main.py --abstract "..." --format json ### How It Works Abstract Analysis: Extracts key terms, methodology, and research focus Field Classification: Identifies the primary research domain Journal Matching: Compares content against journal scopes and aims Impact Factor Filtering: Applies IF constraints if specified Ranking: Scores and ranks journals by relevance and impact ### Technical Details Difficulty: Medium Approach: Keyword extraction + journal database matching Data Source: Journal metadata from references/journals.json Algorithm: TF-IDF + cosine similarity for scope matching ### References references/journals.json - Journal database with impact factors and scopes references/fields.json - Research field classifications references/scoring_weights.json - Algorithm tuning parameters ### Notes Journal database should be updated periodically (quarterly recommended) Impact factor data sourced from Journal Citation Reports (JCR) Scope descriptions parsed from official journal websites For emerging fields, manual curation may be needed ### Risk Assessment Risk IndicatorAssessmentLevelCode ExecutionPython/R scripts executed locallyMediumNetwork AccessNo external API callsLowFile System AccessRead input files, write output filesMediumInstruction TamperingStandard prompt guidelinesLowData ExposureOutput files saved to workspaceLow ### Security Checklist No hardcoded credentials or API keys No unauthorized file system access (../) Output does not expose sensitive information Prompt injection protections in place Input file paths validated (no ../ traversal) Output directory restricted to workspace Script execution in sandboxed environment Error messages sanitized (no stack traces exposed) Dependencies audited ### Prerequisites # Python dependencies pip install -r requirements.txt ### Success Metrics Successfully executes main functionality Output meets quality standards Handles edge cases gracefully Performance is acceptable ### Test Cases Basic Functionality: Standard input → Expected output Edge Case: Invalid input → Graceful error handling Performance: Large dataset → Acceptable processing time ### Lifecycle Status Current Stage: Draft Next Review Date: 2026-03-06 Known Issues: None Planned Improvements: Performance optimization Additional feature support ## Trust - Source: tencent - Verification: Indexed source record - Publisher: AIPOCH-AI - Version: 1.0.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-04-30T00:43:58.932Z - Expires at: 2026-05-07T00:43:58.932Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/journal-matchmaker) - [Send to Agent page](https://openagent3.xyz/skills/journal-matchmaker/agent) - [JSON manifest](https://openagent3.xyz/skills/journal-matchmaker/agent.json) - [Markdown brief](https://openagent3.xyz/skills/journal-matchmaker/agent.md) - [Download page](https://openagent3.xyz/downloads/journal-matchmaker)