{"eval":{"version":"openagentskill-skill-eval-v1","slug":"18601949127-didicallcar","name":"DiDiCallCar","generated_at":"2026-07-04T01:04:32.694Z","task_input":"Evaluate DiDiCallCar before installing it in an AI agent workflow","status":"review","score":68,"risk_level":"medium","decision":{"recommendation":"manual_review","reason":"Test manually in an isolated workspace and compare against safer alternatives.","auto_install_allowed":false,"policy":"review","human_review_required":true},"task_fit":{"score":84,"suited_tasks":["Document processing workflows","Claude Code teams","teams that value GitHub adoption signals","Read uploaded files","Extract structured fields","Prepare clean context for downstream agents","Navigate pages","Click and type safely"],"suited_agents":["Java","OCR","Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"]},"install":{"command":"npx skills add 18601949127/DiDiCallCar","ready":true,"policy":"review","safety_label":"Avoid automatic install","targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx skills add 18601949127/DiDiCallCar"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"DiDiCallCar\" agent skill from https://github.com/18601949127/DiDiCallCar. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"DiDiCallCar\" as a Claude Code skill from https://github.com/18601949127/DiDiCallCar. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"DiDiCallCar\" from https://github.com/18601949127/DiDiCallCar into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."}]},"trust":{"score":78,"label":"Strong shortlist","version":"trust-score-v4","evidence":{"stars":"1.2K GitHub stars","repoActivity":"1.2K stars, 385 forks","lastPushed":"7y since push","license":"Unknown","repository":"https://github.com/18601949127/DiDiCallCar","install":"npx skills add 18601949127/DiDiCallCar","installSafety":"standard package or runtime install path","permissionSurface":"database access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"}},"audit":{"score":69,"risk_level":"needs_review","risk_label":"Needs review","warnings":["License is unclear","Repository appears stale","Repository looks stale","Quality score needs review","Recent maintenance: 7y since push","License clarity: Unknown"]},"safety_gate":{"score":49,"tier":"experimental","label":"Experimental","auto_install_policy":"review","blocked":false,"permission_hints":[{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"},{"id":"database","label":"Database access","reason":"Skill may inspect schemas, query databases, or work with persistent stores.","severity":"medium"}],"policy_warnings":["License is unclear"]},"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate DiDiCallCar before installing it in an AI agent workflow","document-processing","Document processing workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add 18601949127/DiDiCallCar"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add 18601949127/DiDiCallCar"]},{"id":"trust_score","label":"Trust score","status":"warn","score":78,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","1.2K GitHub stars","Unknown"]},{"id":"audit_score","label":"Audit score","status":"warn","score":69,"required_for_auto_install":true,"detail":"Needs review","evidence":["License is unclear"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":49,"required_for_auto_install":true,"detail":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","evidence":["Test manually in an isolated workspace and compare against safer alternatives.","License is unclear"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":90,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"warn","score":42,"required_for_auto_install":true,"detail":"Unknown","evidence":["Unknown"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"fail","score":22,"required_for_auto_install":false,"detail":"7y since push","evidence":["7y since push"]},{"id":"permission_surface","label":"Permission surface","status":"pass","score":88,"required_for_auto_install":true,"detail":"database access","evidence":["Network access: medium","Filesystem access: medium","Database access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"pass","score":82,"required_for_auto_install":false,"detail":"Alternative skills are available for comparison.","evidence":["microsoft-markitdown","paddlepaddle-paddleocr","stirling-tools-stirling-pdf","tesseract-ocr-tesseract"]}],"blockers":[],"warnings":["Trust score: Good trust signals with a few areas worth checking before rollout.","Audit score: Needs review","Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","License clarity: Unknown","License is unclear","Repository appears stale","Repository looks stale","Quality score needs review","Recent maintenance: 7y since push"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"do_not_use_when":["teams that require actively maintained dependencies","production agents without a repository review","Repository looks stale","License is unclear","Repository appears stale","Quality score needs review","Recent maintenance: 7y since push","License clarity: Unknown"],"alternatives":[{"slug":"microsoft-markitdown","name":"Markitdown","url":"https://www.openagentskill.com/skills/microsoft-markitdown","stars":156110,"install_command":"npx skills add microsoft/markitdown","trust_score":90,"audit_score":92},{"slug":"paddlepaddle-paddleocr","name":"PaddleOCR","url":"https://www.openagentskill.com/skills/paddlepaddle-paddleocr","stars":83080,"install_command":"npx skills add PaddlePaddle/PaddleOCR","trust_score":94,"audit_score":95},{"slug":"stirling-tools-stirling-pdf","name":"Stirling PDF","url":"https://www.openagentskill.com/skills/stirling-tools-stirling-pdf","stars":81218,"install_command":"npx skills add Stirling-Tools/Stirling-PDF","trust_score":87,"audit_score":92},{"slug":"tesseract-ocr-tesseract","name":"Tesseract","url":"https://www.openagentskill.com/skills/tesseract-ocr-tesseract","stars":74690,"install_command":"npx skills add tesseract-ocr/tesseract","trust_score":92,"audit_score":95}],"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"18601949127-didicallcar","name":"DiDiCallCar","description":"这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能：  1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL),  and UI.  1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location  and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user. ","category":"document-processing","url":"https://www.openagentskill.com/skills/18601949127-didicallcar","repository":"https://github.com/18601949127/DiDiCallCar","github_repo":"18601949127/DiDiCallCar"},"suited_tasks":["Document processing workflows","Claude Code teams","teams that value GitHub adoption signals","Read uploaded files","Extract structured fields","Prepare clean context for downstream agents","Navigate pages","Click and type safely"],"suited_agents":["Java","OCR","Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add 18601949127/DiDiCallCar","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx skills add 18601949127/DiDiCallCar"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"DiDiCallCar\" agent skill from https://github.com/18601949127/DiDiCallCar. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"DiDiCallCar\" as a Claude Code skill from https://github.com/18601949127/DiDiCallCar. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"DiDiCallCar\" from https://github.com/18601949127/DiDiCallCar into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user."}],"handoff_url":"https://www.openagentskill.com/api/skills/18601949127-didicallcar/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/18601949127-didicallcar"},"trust":{"score":78,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"1.2K GitHub stars","repoActivity":"1.2K stars, 385 forks","lastPushed":"7y since push","license":"Unknown","repository":"https://github.com/18601949127/DiDiCallCar","install":"npx skills add 18601949127/DiDiCallCar","installSafety":"standard package or runtime install path","permissionSurface":"database access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["document-processing","ocr","documents","extraction","android","call"],"known_risks":["License is unclear","Repository looks stale","Quality score needs review","Recent maintenance: 7y since push","License clarity: Unknown"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":69,"risk_level":"needs_review","risk_label":"Needs review","warnings":["License is unclear","Repository appears stale","Repository looks stale","Quality score needs review","Recent maintenance: 7y since push","License clarity: Unknown"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":66,"label":"Promising"},"supply":{"track":"Research and knowledge work","scenario":"Document processing","maintenance":"7y since push","risk":"Needs review"},"alternative_skills":[{"slug":"microsoft-markitdown","name":"Markitdown","url":"https://www.openagentskill.com/skills/microsoft-markitdown","stars":156110,"install_command":"npx skills add microsoft/markitdown","trust_score":90,"audit_score":92},{"slug":"paddlepaddle-paddleocr","name":"PaddleOCR","url":"https://www.openagentskill.com/skills/paddlepaddle-paddleocr","stars":83080,"install_command":"npx skills add PaddlePaddle/PaddleOCR","trust_score":94,"audit_score":95},{"slug":"stirling-tools-stirling-pdf","name":"Stirling PDF","url":"https://www.openagentskill.com/skills/stirling-tools-stirling-pdf","stars":81218,"install_command":"npx skills add Stirling-Tools/Stirling-PDF","trust_score":87,"audit_score":92},{"slug":"tesseract-ocr-tesseract","name":"Tesseract","url":"https://www.openagentskill.com/skills/tesseract-ocr-tesseract","stars":74690,"install_command":"npx skills add tesseract-ocr/tesseract","trust_score":92,"audit_score":95}],"do_not_use_when":["teams that require actively maintained dependencies","production agents without a repository review","Repository looks stale","License is unclear","Repository appears stale","Quality score needs review","Recent maintenance: 7y since push","License clarity: Unknown"],"agent_contract":{"task_input":"Evaluate DiDiCallCar before installing it in an AI agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 78/100 Strong shortlist","Audit: 69/100 Needs review","Safety: 49/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"18601949127-didicallcar (DiDiCallCar)","install_command":"npx skills add 18601949127/DiDiCallCar","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"18601949127-didicallcar","task":"Evaluate DiDiCallCar before installing it in an AI agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/18601949127-didicallcar","api":"https://www.openagentskill.com/api/agent/skills/18601949127-didicallcar","audit":"https://www.openagentskill.com/skills/18601949127-didicallcar/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=18601949127-didicallcar&task=Evaluate%20DiDiCallCar%20before%20installing%20it%20in%20an%20AI%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Evaluate%20DiDiCallCar%20before%20installing%20it%20in%20an%20AI%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Evaluate%20DiDiCallCar%20before%20installing%20it%20in%20an%20AI%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/18601949127-didicallcar/install","manifest":"https://www.openagentskill.com/api/registry/manifest/18601949127-didicallcar"}},"endpoints":{"web":"https://www.openagentskill.com/skills/18601949127-didicallcar","api":"https://www.openagentskill.com/api/agent/skills/18601949127-didicallcar","eval":"https://www.openagentskill.com/api/agent/evals?slug=18601949127-didicallcar","audit":"https://www.openagentskill.com/skills/18601949127-didicallcar/audit","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Evaluate%20DiDiCallCar%20before%20installing%20it%20in%20an%20AI%20agent%20workflow&agent=codex&max_risk=medium"}},"meta":{"endpoint":"/api/agent/evals","mode":"skill_eval","purpose":"Pre-install eval contract for a single skill. 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