{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-kind-lingtwig","slug":"npm-kind-lingtwig","name":"@kind-ling/twig","type":"mcp","url":"https://www.npmjs.com/package/@kind-ling/twig","page_url":"https://unfragile.ai/npm-kind-lingtwig","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-kind-lingtwig__cap_0","uri":"capability://tool.use.integration.mcp.tool.description.optimization.via.llm.analysis","name":"mcp tool description optimization via llm analysis","description":"Analyzes tool definitions and their descriptions through LLM inference to identify clarity, completeness, and discoverability gaps that prevent agent selection. Uses prompt engineering to evaluate descriptions against agent decision-making criteria, generating structured feedback on how to improve tool adoption by AI agents. The optimizer examines parameter documentation, use-case clarity, and schema expressiveness to surface optimization opportunities.","intents":["I want agents to actually use my custom MCP tools instead of ignoring them","I need to understand why my tool descriptions aren't being selected by LLM-based agents","I want to improve my tool's discoverability in agent tool-calling scenarios","I need to audit my tool definitions for clarity and completeness from an agent's perspective"],"best_for":["MCP server developers building custom tool ecosystems","Teams deploying agent-based systems with custom tool integrations","Developers optimizing tool adoption rates in multi-agent environments"],"limitations":["Requires external LLM API calls, adding latency and cost per optimization pass","Optimization quality depends on underlying LLM capability and prompt engineering","No built-in A/B testing framework to validate that optimizations actually improve agent selection rates","Limited to analyzing static tool definitions; cannot measure real agent behavior patterns"],"requires":["Node.js 16+","MCP server with tool definitions (JSON schema format)","API key for LLM provider (OpenAI, Anthropic, or compatible)","@kind-ling/twig npm package"],"input_types":["JSON tool schema (MCP format)","Tool description strings","Parameter definitions with type hints"],"output_types":["Structured optimization recommendations (JSON)","Revised description suggestions (text)","Clarity and completeness scores (numeric)"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-kind-lingtwig__cap_1","uri":"capability://tool.use.integration.tool.schema.analysis.and.completeness.validation","name":"tool schema analysis and completeness validation","description":"Parses and validates MCP tool schema definitions to identify missing or ambiguous parameter documentation, incomplete type specifications, and unclear use-case descriptions that reduce agent selection probability. Performs structural analysis of JSON schemas to detect gaps in required fields, examples, and constraint definitions that agents rely on for tool understanding.","intents":["I want to validate that my tool schema is complete before deploying to agents","I need to find missing parameter descriptions or type hints in my tool definitions","I want to ensure my tool schema follows patterns that agents can easily understand","I need to identify which parts of my tool definition are causing agent confusion"],"best_for":["MCP server maintainers ensuring schema quality","Teams standardizing tool definition patterns across multiple services","Developers debugging why agents fail to invoke their tools correctly"],"limitations":["Validation is schema-structural only; cannot detect logical inconsistencies in tool behavior","Does not test actual agent invocation behavior, only definition completeness","Limited to MCP schema format; cannot validate tools in other formats (OpenAPI, etc.)","No built-in remediation — only identifies gaps, requires manual fixes"],"requires":["MCP tool definition in JSON schema format","Node.js 16+","@kind-ling/twig npm package"],"input_types":["JSON tool schema (MCP format)","Tool metadata (name, description, category)"],"output_types":["Validation report (JSON)","List of missing/incomplete fields (structured)","Severity-ranked issues (numeric scores)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-kind-lingtwig__cap_2","uri":"capability://text.generation.language.agent.centric.tool.description.rewriting.with.llm.generation","name":"agent-centric tool description rewriting with llm generation","description":"Generates improved tool descriptions optimized for LLM agent comprehension by reframing existing descriptions to emphasize use-case clarity, parameter necessity, and invocation patterns that agents prioritize. Uses prompt engineering to produce descriptions that highlight when and why an agent should select this tool, incorporating agent decision-making heuristics into the generated text.","intents":["I want to rewrite my tool description to make it more attractive to agents","I need help explaining my tool's purpose in a way agents will understand and prioritize","I want to generate multiple description variants and test which one agents prefer","I need to add use-case examples that help agents understand when to invoke this tool"],"best_for":["MCP tool developers optimizing for agent adoption","Teams A/B testing tool descriptions to improve selection rates","Developers scaling tool ecosystems and needing consistent description quality"],"limitations":["Generated descriptions may be verbose or include unnecessary detail for human users","No guarantee that agent-optimized descriptions improve actual selection rates without testing","Requires LLM API calls, adding cost and latency per generation","Cannot generate descriptions for tools with unclear or poorly documented original intent"],"requires":["Original tool description (text)","Tool schema and parameters (JSON)","API key for LLM provider","Node.js 16+"],"input_types":["Existing tool description (text)","Tool schema (JSON)","Use-case context (optional text)"],"output_types":["Rewritten description (text)","Multiple description variants (text array)","Optimization rationale (text explanation)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-kind-lingtwig__cap_3","uri":"capability://data.processing.analysis.tool.adoption.metrics.and.scoring.system","name":"tool adoption metrics and scoring system","description":"Calculates quantitative scores for tool descriptions based on agent-selection factors including clarity, specificity, use-case coverage, and parameter documentation completeness. Provides numeric ratings that help developers understand relative tool quality and track improvements over time, using weighted scoring criteria derived from agent decision-making patterns.","intents":["I want a numeric score to measure how agent-friendly my tool description is","I need to track whether my description improvements actually increase tool quality","I want to compare adoption potential across multiple tools in my ecosystem","I need to identify which aspects of my tool definition are weakest from an agent perspective"],"best_for":["Teams managing large tool ecosystems needing quality metrics","Developers tracking optimization progress over time","Organizations benchmarking tool quality across teams"],"limitations":["Scores are heuristic-based and may not correlate with actual agent selection behavior","No built-in feedback loop to validate scoring accuracy against real agent usage","Scoring weights are fixed; cannot be customized per agent type or use case","Metrics are descriptive only — do not predict actual adoption rates"],"requires":["Tool schema and description (JSON/text)","Node.js 16+","@kind-ling/twig npm package"],"input_types":["Tool schema (JSON)","Tool description (text)","Tool metadata (name, category)"],"output_types":["Overall adoption score (0-100 numeric)","Component scores (clarity, specificity, coverage, etc.)","Score breakdown with rationale (structured JSON)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-kind-lingtwig__cap_4","uri":"capability://tool.use.integration.batch.tool.optimization.with.multi.tool.analysis","name":"batch tool optimization with multi-tool analysis","description":"Processes multiple MCP tool definitions in a single operation, analyzing them collectively to identify patterns, inconsistencies, and relative quality gaps across a tool ecosystem. Enables comparative analysis where tools are evaluated not just individually but in context of other available tools, helping agents understand differentiation and selection criteria.","intents":["I want to optimize all my tools at once rather than one at a time","I need to ensure consistency in description style and quality across my tool ecosystem","I want to identify which tools are most likely to be selected by agents","I need to understand how my tools compete with each other for agent selection"],"best_for":["Teams managing 10+ custom MCP tools","Organizations standardizing tool quality across multiple services","Developers building comprehensive tool ecosystems for agent platforms"],"limitations":["Batch processing requires multiple LLM API calls, increasing cost and latency","Comparative analysis assumes tools serve similar purposes; may not apply to diverse tool sets","No built-in deduplication detection — cannot identify redundant or overlapping tools","Results are relative; absolute quality still depends on individual tool design"],"requires":["Multiple tool schemas (JSON array)","Node.js 16+","API key for LLM provider","@kind-ling/twig npm package"],"input_types":["Array of tool schemas (JSON)","Tool metadata (names, descriptions, categories)"],"output_types":["Per-tool optimization recommendations (JSON array)","Ecosystem-wide consistency report (structured)","Comparative quality rankings (numeric)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"moderate","permissions":["Node.js 16+","MCP server with tool definitions (JSON schema format)","API key for LLM provider (OpenAI, Anthropic, or compatible)","@kind-ling/twig npm package","MCP tool definition in JSON schema format","Original tool description (text)","Tool schema and parameters (JSON)","API key for LLM provider","Tool schema and description (JSON/text)","Multiple tool schemas (JSON array)"],"failure_modes":["Requires external LLM API calls, adding latency and cost per optimization pass","Optimization quality depends on underlying LLM capability and prompt engineering","No built-in A/B testing framework to validate that optimizations actually improve agent selection rates","Limited to analyzing static tool definitions; cannot measure real agent behavior patterns","Validation is schema-structural only; cannot detect logical inconsistencies in tool behavior","Does not test actual agent invocation behavior, only definition completeness","Limited to MCP schema format; cannot validate tools in other formats (OpenAPI, etc.)","No built-in remediation — only identifies gaps, requires manual fixes","Generated descriptions may be verbose or include unnecessary detail for human users","No guarantee that agent-optimized descriptions improve actual selection rates without testing","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.2,"ecosystem":0.3,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-05-03T14:24:00.084Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-kind-lingtwig","compare_url":"https://unfragile.ai/compare?artifact=npm-kind-lingtwig"}},"signature":"N42VaqlbCtUF5SIOWze8mARwWbodb3AnlvEljed/JyWI9mksnT7aI+e2wgGINitqb/se3tGafJFEXKneCLpqDw==","signedAt":"2026-06-22T09:16:50.871Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-kind-lingtwig","artifact":"https://unfragile.ai/npm-kind-lingtwig","verify":"https://unfragile.ai/api/v1/verify?slug=npm-kind-lingtwig","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}