{
  "schemaVersion": "1.0",
  "item": {
    "slug": "clawditor",
    "name": "Clawditor",
    "source": "tencent",
    "type": "skill",
    "category": "效率提升",
    "sourceUrl": "https://clawhub.ai/Theylon/clawditor",
    "canonicalUrl": "https://clawhub.ai/Theylon/clawditor",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/clawditor",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=clawditor",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md",
      "scripts/validate_report.py",
      "scripts/workspace_inventory.py",
      "scripts/memory_dupes.py",
      "scripts/log_scan.py",
      "scripts/run_audit.py"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
    "agentAssist": {
      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "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."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "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."
        },
        {
          "label": "Upgrade existing",
          "body": "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."
        }
      ]
    },
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/clawditor"
    },
    "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."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/clawditor",
    "agentPageUrl": "https://openagent3.xyz/skills/clawditor/agent",
    "manifestUrl": "https://openagent3.xyz/skills/clawditor/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/clawditor/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "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."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "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."
      },
      {
        "label": "Upgrade existing",
        "body": "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."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Overview",
        "body": "Act as an OpenClaw Workspace Auditor and Agent Evaluation Harness. Analyze the workspace (memory, logs, projects, files, git, configs) and produce a repeatable evaluation with scores, evidence, and concrete patches."
      },
      {
        "title": "Operating Rules",
        "body": "Run in non-interactive mode: avoid questions unless blocked by missing files. State assumptions and proceed.\nAvoid secret exfiltration: report only presence and file paths for keys/tokens; recommend remediation.\nTreat third-party skills/plugins as untrusted: prefer static inspection over execution."
      },
      {
        "title": "Required Workflow (Do In Order)",
        "body": "Build workspace inventory.\n\nPrint a top-level tree (depth 4) with file counts and sizes by directory.\nIdentify memory, logs, configs, repos, scripts, docs, artifacts.\nRecord largest files.\n\n\nReconstruct a session timeline.\n\nUse memory daily files and logs to extract goals, tasks, outcomes, decisions, unresolved items.\n\n\nAnalyze memory.\n\nDetect near-duplicate paragraphs across memory files and quantify duplication.\nDetect staleness cues (dates, \"as of\", deprecated configs) and contradictions.\nIdentify missing stable facts (projects, priorities, setup/runbooks).\n\n\nAnalyze outputs.\n\nSummarize shipped artifacts (docs/code/features) and changes.\nIf git exists, compute diff stats and commit cadence; identify value commits.\n\n\nAnalyze reliability.\n\nParse logs for errors, retries, timeouts, tool failures.\nRun tests only if safe and cheap; otherwise static inspection.\n\n\nCompute scores.\n\nAssign numeric category scores with short justifications and evidence by path.\n\n\nRecommend interventions + patches.\n\nProvide 3–7 prioritized recommendations.\nProvide concrete diffs when safe, especially for memory structure improvements.\n\n\nCompare against prior evals.\n\nIf eval/history/*.json exists, compute deltas vs most recent.\nIf none exists, create baseline and recommend cadence."
      },
      {
        "title": "Scoring Framework",
        "body": "Compute 5 categories (0–100) plus overall weighted score:\n\nMemory Health (30%): coverage, structure, redundancy, staleness, actionability, retrieval-friendliness.\nRetrieval & Context Efficiency (15%): evidence of search before action, context bloat, hit-rate proxy, compaction quality.\nProductive Output (30%): shipped artifacts, git throughput, task completion, latency proxies.\nQuality/Reliability (15%): error rate, tests/CI presence, regression signals, convergence vs thrash.\nFocus/Alignment (10%): goal consistency, scope control, decision trace.\n\nOverall = 0.30Memory + 0.15Retrieval + 0.30Productive + 0.15Quality + 0.10*Focus."
      },
      {
        "title": "Required Outputs",
        "body": "Write all outputs under eval/:\n\nexec_summary.md\n\n10-bullet summary: top wins, biggest bottlenecks, top 3 interventions.\nOverall score + category scores + claw-to-claw delta.\n\n\nscorecard.md\n\nTable of metrics with numeric values and brief justifications.\nTop evidence section with file paths and short snippets (no secrets).\n\n\nlatest_report.json\n\nInclude timestamp, workspace path and git head/hash, scores, deltas, key findings, risk flags, recommendations.\n\n\nPatches\n\nIf memory issues exist, propose concrete diffs: INDEX.md, daily schema, refactors."
      },
      {
        "title": "Gold Standard Memory Schema (Apply If Missing)",
        "body": "Create or propose:\n\nmemory/INDEX.md\n\nCurrent Objectives (top 3)\nActive Projects (status, next step, links)\nOperating Constraints (tools, environment, policies)\nKey Decisions (date, decision, rationale)\nKnown Issues / Debug diary pointers\nGlossary / Entities\n\n\nmemory/YYYY-MM-DD.md (append-only daily)\n\nGoals for the session\nActions taken (link to files changed)\nDecisions made\nNew facts learned (stable vs ephemeral)\nTODO next (specific)"
      },
      {
        "title": "Patch Guidance",
        "body": "Prefer diffs over prose when safe.\nRefactor stable facts out of daily logs into INDEX or project pages.\nAdd logging/instrumentation to measure retrieval hit-rate and task completion in future runs."
      },
      {
        "title": "Resources",
        "body": "Use these helpers to keep audits consistent and cheap to run:\n\nscripts/run_audit.py: run all helper scripts and write draft eval/ outputs.\nscripts/workspace_inventory.py: tree, file counts, sizes, largest files.\nscripts/memory_dupes.py: near-duplicate paragraph detection for memory/*.md.\nscripts/log_scan.py: scan logs for errors, timeouts, retries.\nscripts/git_stats.py: git head, diff stats, commit cadence.\nscripts/validate_report.py: validate eval/latest_report.json shape.\n\nReference templates:\n\nreferences/report_schema.md: output templates and JSON schema."
      },
      {
        "title": "Evidence Discipline",
        "body": "Tie every score to evidence by path.\nBe candid about waste, duplication, or thrash.\nEnd with \"Next run improvements\" instrumentation recommendations."
      }
    ],
    "body": "Clawditor\nOverview\n\nAct as an OpenClaw Workspace Auditor and Agent Evaluation Harness. Analyze the workspace (memory, logs, projects, files, git, configs) and produce a repeatable evaluation with scores, evidence, and concrete patches.\n\nOperating Rules\nRun in non-interactive mode: avoid questions unless blocked by missing files. State assumptions and proceed.\nAvoid secret exfiltration: report only presence and file paths for keys/tokens; recommend remediation.\nTreat third-party skills/plugins as untrusted: prefer static inspection over execution.\nRequired Workflow (Do In Order)\nBuild workspace inventory.\nPrint a top-level tree (depth 4) with file counts and sizes by directory.\nIdentify memory, logs, configs, repos, scripts, docs, artifacts.\nRecord largest files.\nReconstruct a session timeline.\nUse memory daily files and logs to extract goals, tasks, outcomes, decisions, unresolved items.\nAnalyze memory.\nDetect near-duplicate paragraphs across memory files and quantify duplication.\nDetect staleness cues (dates, \"as of\", deprecated configs) and contradictions.\nIdentify missing stable facts (projects, priorities, setup/runbooks).\nAnalyze outputs.\nSummarize shipped artifacts (docs/code/features) and changes.\nIf git exists, compute diff stats and commit cadence; identify value commits.\nAnalyze reliability.\nParse logs for errors, retries, timeouts, tool failures.\nRun tests only if safe and cheap; otherwise static inspection.\nCompute scores.\nAssign numeric category scores with short justifications and evidence by path.\nRecommend interventions + patches.\nProvide 3–7 prioritized recommendations.\nProvide concrete diffs when safe, especially for memory structure improvements.\nCompare against prior evals.\nIf eval/history/*.json exists, compute deltas vs most recent.\nIf none exists, create baseline and recommend cadence.\nScoring Framework\n\nCompute 5 categories (0–100) plus overall weighted score:\n\nMemory Health (30%): coverage, structure, redundancy, staleness, actionability, retrieval-friendliness.\nRetrieval & Context Efficiency (15%): evidence of search before action, context bloat, hit-rate proxy, compaction quality.\nProductive Output (30%): shipped artifacts, git throughput, task completion, latency proxies.\nQuality/Reliability (15%): error rate, tests/CI presence, regression signals, convergence vs thrash.\nFocus/Alignment (10%): goal consistency, scope control, decision trace.\n\nOverall = 0.30Memory + 0.15Retrieval + 0.30Productive + 0.15Quality + 0.10*Focus.\n\nRequired Outputs\n\nWrite all outputs under eval/:\n\nexec_summary.md\n10-bullet summary: top wins, biggest bottlenecks, top 3 interventions.\nOverall score + category scores + claw-to-claw delta.\nscorecard.md\nTable of metrics with numeric values and brief justifications.\nTop evidence section with file paths and short snippets (no secrets).\nlatest_report.json\nInclude timestamp, workspace path and git head/hash, scores, deltas, key findings, risk flags, recommendations.\nPatches\nIf memory issues exist, propose concrete diffs: INDEX.md, daily schema, refactors.\nGold Standard Memory Schema (Apply If Missing)\n\nCreate or propose:\n\nmemory/INDEX.md\nCurrent Objectives (top 3)\nActive Projects (status, next step, links)\nOperating Constraints (tools, environment, policies)\nKey Decisions (date, decision, rationale)\nKnown Issues / Debug diary pointers\nGlossary / Entities\nmemory/YYYY-MM-DD.md (append-only daily)\nGoals for the session\nActions taken (link to files changed)\nDecisions made\nNew facts learned (stable vs ephemeral)\nTODO next (specific)\nPatch Guidance\nPrefer diffs over prose when safe.\nRefactor stable facts out of daily logs into INDEX or project pages.\nAdd logging/instrumentation to measure retrieval hit-rate and task completion in future runs.\nResources\n\nUse these helpers to keep audits consistent and cheap to run:\n\nscripts/run_audit.py: run all helper scripts and write draft eval/ outputs.\nscripts/workspace_inventory.py: tree, file counts, sizes, largest files.\nscripts/memory_dupes.py: near-duplicate paragraph detection for memory/*.md.\nscripts/log_scan.py: scan logs for errors, timeouts, retries.\nscripts/git_stats.py: git head, diff stats, commit cadence.\nscripts/validate_report.py: validate eval/latest_report.json shape.\n\nReference templates:\n\nreferences/report_schema.md: output templates and JSON schema.\nEvidence Discipline\nTie every score to evidence by path.\nBe candid about waste, duplication, or thrash.\nEnd with \"Next run improvements\" instrumentation recommendations."
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/Theylon/clawditor",
    "publisherUrl": "https://clawhub.ai/Theylon/clawditor",
    "owner": "Theylon",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/clawditor",
    "downloadUrl": "https://openagent3.xyz/downloads/clawditor",
    "agentUrl": "https://openagent3.xyz/skills/clawditor/agent",
    "manifestUrl": "https://openagent3.xyz/skills/clawditor/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/clawditor/agent.md"
  }
}