{"id":"8bab0bfa-6ea1-41b5-81d2-07d0401af40c","entityType":"agent","slug":"crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33","name":"Crawled e2b.dev d1a92b1a","canonicalUrl":"https://www.xpersona.co/agent/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33","canonicalPath":"/agent/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33","generatedAt":"2026-10-09T22:58:36.519Z","source":"GITHUB_REPOS","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-04-14T23:26:25.608Z","emptyReason":null},"description":"= StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbo... = StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbox.run_code(code) result = execution.text print (result) “~/lchain.py” 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ from llama_index.core.tools import FunctionTool f","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. 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Standard integration tests and API key provisioning are required before connecting this to production workloads.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":[]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_REPOS","generatedAt":"2026-10-09T22:58:36.519Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crawl-fda52d641c6b482bda7b-d1a92b1a9e93bc4f7a33/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"high","updatedAt":"2026-04-14T23:26:25.608Z","emptyReason":null},"readme":" = StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbox.run_code(code) result = execution.text print (result) “~/lchain.py” 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ from llama_index.core.tools import FunctionTool from llama_index.llms.openai import OpenAI from llama_index.core.agent import ReActAgent from e2b_code_interpreter import Sandbox # Define the tool def execute_python ( code: str ): with Sandbox() as sandbox: execution = sandbox.run_code(code) return execution.text e2b_interpreter_tool = FunctionTool.from_defaults( name= \"execute_python\" , description= \"Execute python code in a Jupyter notebook cell and return result\" , fn=execute_python ) # Initialize LLM llm = OpenAI(model=","readmeExcerpt":"= StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbox.run_code(code) result = execution.text print (result) “~/lchain.py” 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ from llama_index.core.tools import FunctionTool f","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":[],"docsSourceLabel":"GITHUB REPOS","editorialOverview":"= StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbo... = StrOutputParser() # Create the chain chain = prompt_template | llm | output_parser # Run the chain code = chain.invoke({ \"input\" : prompt}) # Execute code in E2B Sandbox with Sandbox() as sandbox: execution = sandbox.run_code(code) result = execution.text print (result) “~/lchain.py” 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ from llama_index.core.tools import FunctionTool f","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":421,"uniquenessScore":62,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-04-14T23:26:25.608Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-04-14T23:26:25.608Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"agent-directory","verified":false,"confidence":"low","updatedAt":"2026-10-09T22:58:36.519Z","emptyReason":"No close protocol neighbors were found."},"items":[],"links":{"hub":"/agent","source":"/agent/source/github_repos","protocols":[]}}}