# Send input classification 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": "input-classification-v1", "name": "input classification", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/omprasad122007-rgb/input-classification-v1", "canonicalUrl": "https://clawhub.ai/omprasad122007-rgb/input-classification-v1", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/input-classification-v1", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=input-classification-v1", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "references/classification-models.md", "references/system-integration.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "input-classification-v1", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-04T23:06:49.677Z", "expiresAt": "2026-05-11T23:06:49.677Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=input-classification-v1", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=input-classification-v1", "contentDisposition": "attachment; filename=\"input-classification-v1-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "input-classification-v1" }, "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/input-classification-v1" }, "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/input-classification-v1", "downloadUrl": "https://openagent3.xyz/downloads/input-classification-v1", "agentUrl": "https://openagent3.xyz/skills/input-classification-v1/agent", "manifestUrl": "https://openagent3.xyz/skills/input-classification-v1/agent.json", "briefUrl": "https://openagent3.xyz/skills/input-classification-v1/agent.md" } } ``` ## Documentation ### 1. Skill Name Input Classification System Identifier: input-classification-system ### 2. Version 1.0 This is the initial release of the Input Classification System skill. ### 3. Skill Purpose Provide a deterministic, rule-based classification system that enables the Main Agent to categorize clarified user input into exactly one primary task category, assign execution complexity, assess risk level, and determine confidence score before any task decomposition or execution planning occurs. Measurable Objectives: Achieve 100% single-category classification (no ambiguous multi-category outputs) Provide deterministic tie-breaking for all edge cases Assign complexity levels using measurable thresholds Calculate confidence scores with explicit formulas Route ambiguous inputs to clarification with specific triggers ### 4. What This Skill Does Classifies clarified input into exactly one primary category from a fixed list Assigns complexity level based on measurable operation counts and time estimates Calculates risk level based on impact scope and reversibility criteria Computes confidence score using explicit scoring factors Determines if input requires additional clarification Sets the appropriate state transition after classification Applies deterministic tie-breaking logic when multiple categories match Validates that input has been clarified before classification Logs all classification decisions with full context Provides secondary tags for additional context (maximum 3) Enforces boundary definitions between categories Triggers escalation for high-risk or low-confidence classifications Prevents misclassification through explicit rules Outputs structured ClassificationResult for downstream systems Maintains audit trail for all classification decisions ### 5. What This Skill Must Not Do Must not perform task decomposition or breakdown Must not solve or execute any tasks Must not create execution plans or strategies Must not apply emotional reasoning or sentiment analysis Must not assign multiple primary categories to a single input Must not overlap with Clarification System responsibilities Must not modify the original input content Must not make assumptions about user intent without explicit indicators Must not skip complexity assessment for any classification Must not bypass risk assessment for any classification Must not assign confidence scores below threshold without escalation Must not classify inputs that have not been clarified first Must not use probabilistic or non-deterministic classification methods Must not ignore tie-breaking rules when categories conflict Must not proceed to execution without setting state transition ### 6. Activation Conditions This skill activates when ALL of the following conditions are met: Clarification Complete: Input has been processed by the Clarification System and marked as clarified No Pending Questions: No outstanding clarification questions remain Classification Not Yet Performed: Input has not been previously classified Valid Input Structure: Input contains recognizable task indicators Pre-Activation Checklist: Input marked as "clarified" by Clarification System No clarification questions pending Input contains actionable request Input is not empty or malformed Do NOT activate if: Input is still being clarified Input is a clarification question itself Input is a response to a clarification question Input has already been classified ### 7. Classification Categories The following 15 categories form the fixed classification list: CategoryCodeDescriptionCODE_GENERATIONCGWriting, modifying, or generating source codeCODE_REVIEWCRReviewing, analyzing, or auditing existing codeDEBUGGINGDBIdentifying and fixing bugs, errors, or issuesDATA_ANALYSISDAAnalyzing, processing, or visualizing dataFILE_OPERATIONSFOReading, writing, moving, or managing filesDOCUMENTATIONDCCreating or updating documentationREFACTORINGRFRestructuring code without changing behaviorTESTINGTSWriting, running, or managing testsDEPLOYMENTDPDeploying applications or infrastructureRESEARCHRSInvestigating, searching, or gathering informationCONFIGURATIONCFSetting up or modifying configurationsCOMMUNICATIONCMDrafting messages, emails, or communicationsCONVERSIONCVTransforming data or files between formatsANALYSISANGeneral analysis not covered by other categoriesPLANNINGPLCreating plans, strategies, or roadmaps Category Priority Order (for tie-breaking): DEBUGGING (highest - immediate attention needed) DEPLOYMENT CODE_GENERATION REFACTORING TESTING CODE_REVIEW DATA_ANALYSIS CONFIGURATION FILE_OPERATIONS CONVERSION DOCUMENTATION RESEARCH ANALYSIS COMMUNICATION PLANNING (lowest) ### CODE_GENERATION vs CODE_REVIEW CODE_GENERATION: Input requests creating new code or modifying existing code CODE_REVIEW: Input requests analysis of existing code without modifications Boundary: If modification is implied, classify as CODE_GENERATION ### CODE_GENERATION vs REFACTORING CODE_GENERATION: Creating new functionality or features REFACTORING: Restructuring existing code without new functionality Boundary: "Improve performance" without feature change = REFACTORING ### DEBUGGING vs CODE_GENERATION DEBUGGING: Input explicitly mentions errors, bugs, or failures CODE_GENERATION: Input requests new features without error context Boundary: "Fix this bug" = DEBUGGING; "Add error handling" = CODE_GENERATION ### DATA_ANALYSIS vs ANALYSIS DATA_ANALYSIS: Input involves data processing, statistics, or visualization ANALYSIS: Input involves general analysis of concepts, requirements, or situations Boundary: If data files/sets are mentioned = DATA_ANALYSIS ### FILE_OPERATIONS vs CONVERSION FILE_OPERATIONS: Input requests file management (read, write, move, delete) CONVERSION: Input requests format transformation between file types Boundary: "Convert X to Y format" = CONVERSION; "Read file X" = FILE_OPERATIONS ### RESEARCH vs ANALYSIS RESEARCH: Input requests information gathering or investigation ANALYSIS: Input requests evaluation or assessment of known information Boundary: "Find information about X" = RESEARCH; "Evaluate X" = ANALYSIS ### TESTING vs CODE_GENERATION TESTING: Input specifically requests test creation or test execution CODE_GENERATION: Input requests production code Boundary: "Write tests for X" = TESTING; "Write X with tests" = CODE_GENERATION (primary) ### CONFIGURATION vs DEPLOYMENT CONFIGURATION: Input requests setup of settings or configurations DEPLOYMENT: Input requests deployment to environments or infrastructure Boundary: Local setup = CONFIGURATION; Remote/environment setup = DEPLOYMENT ### 9. Single-Primary-Category Rule Rule: Every classified input MUST have exactly one primary category. ### Enforcement Rules No Multi-Category Output: Never output multiple primary categories Tie-Breaking Required: When multiple categories match, apply tie-breaking logic Category Exclusivity: Primary category is mutually exclusive with other primary categories ### Tie-Breaking Logic When input matches multiple categories, apply in order: Step 1: Keyword Dominance Count explicit keyword matches for each candidate category Category with highest keyword count wins If tied, proceed to Step 2 Step 2: Action Verb Analysis Identify primary action verb in input Map action verb to category using verb-to-category mapping If still tied, proceed to Step 3 Step 3: Priority Order Apply category priority order (see Section 7) Higher priority category wins Step 4: Default Fallback If all steps fail, default to ANALYSIS category ### Tie-Breaking Example Input: "Debug and fix the error in the authentication code, then add logging" Keywords: DEBUGGING (debug, fix, error), CODE_GENERATION (add, logging) Action Verb: "Debug" (primary action) → DEBUGGING Result: DEBUGGING (primary), secondary_tags: [CODE_GENERATION] ### 10. Secondary Tag Rules Secondary tags provide additional context without affecting primary routing. ### Rules Maximum 3 Tags: No more than 3 secondary tags per classification No Primary Duplicate: Secondary tags cannot duplicate primary category Related Categories Only: Secondary tags must be from the fixed category list Relevance Threshold: Only add tags with >50% keyword match confidence ### Secondary Tag Selection Process Identify all categories with keyword matches (excluding primary) Calculate relevance score for each (0.0-1.0) Sort by relevance score (descending) Select top 3 with score > 0.5 Add to ClassificationResult ### When to Apply Secondary Tags Input contains multiple distinct sub-tasks Input references multiple technology domains Input implies follow-up work in other categories Input has context from previous interactions in different categories ### When NOT to Apply Secondary Tags Input is single-focused with no additional context Relevance scores are below threshold (0.5) Would duplicate primary category Would exceed 3-tag limit ### Secondary Tag Examples InputPrimarySecondary Tags"Debug the API and update the docs"DEBUGGING[DOCUMENTATION]"Refactor the auth module and add tests"REFACTORING[TESTING]"Analyze sales data and create a report"DATA_ANALYSIS[DOCUMENTATION, COMMUNICATION]"Fix this bug"DEBUGGING[] ### Classification Models Reference For detailed complexity, risk, confidence, and state transition models, see classification-models.md. For system integration, failure conditions, logging, and examples, see system-integration.md. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: omprasad122007-rgb - 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: 2026-05-04T23:06:49.677Z - Expires at: 2026-05-11T23:06:49.677Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/input-classification-v1) - [Send to Agent page](https://openagent3.xyz/skills/input-classification-v1/agent) - [JSON manifest](https://openagent3.xyz/skills/input-classification-v1/agent.json) - [Markdown brief](https://openagent3.xyz/skills/input-classification-v1/agent.md) - [Download page](https://openagent3.xyz/downloads/input-classification-v1)