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shift

Multi-identity delegation for OpenClaw. Turns a single agent into a system of specialized sub-identities (coding, research, quick tasks) each powered by different AI models. Use when: (1) the user asks a coding task (write, debug, implement, refactor, explain code), (2) the user asks for research, analysis, comparison, or explanation, (3) the user asks a quick question, lookup, or reminder, (4) the user asks anything that would benefit from a specialized model. NOT for: trivial greetings, acknowledgments, or meta-conversation about the chat itself. SHIFT handles routing, delegation, sub-identity-to-sub-identity consultation, synthesis, and cost management entirely within one conversation.

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LeoYeAI/openclaw-master-skills
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2026년 7월 20일 02:05
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SKILL.md
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shift
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Multi-identity delegation for OpenClaw. Turns a single agent into a system of specialized sub-identities (coding, research, quick tasks) each powered by different AI models. Use when: (1) the user asks a coding task (write, debug, implement, refactor, explain code), (2) the user asks for research, analysis, comparison, or explanation, (3) the user asks a quick question, lookup, or reminder, (4) the user asks anything that would benefit from a specialized model. NOT for: trivial greetings, acknowledgments, or meta-conversation about the chat itself. SHIFT handles routing, delegation, sub-identity-to-sub-identity consultation, synthesis, and cost management entirely within one conversation.
# SHIFT — Multi-Identity Delegation Skill **One agent. Many specialists. One conversation.** --- ## ⚠️ SECURITY AND PRIVACY — READ BEFORE ENABLING ### What SHIFT Accesses SHIFT reads from your OpenClaw workspace: - `~/.openclaw/workspace/MEMORY.md` — excerpts attached to delegation context - `~/.openclaw/workspace/.shift/config.yaml` — your persona and cost settings - Session files it creates in `~/.openclaw/workspace/.shift/sessions/` SHIFT writes to: - `~/.openclaw/workspace/.shift/sessions/<runId>/` — per-delegation session files - `~/.openclaw/workspace/.shift/cost-tracking.json` — delegation cost tracking - `~/.openclaw/workspace/.shift/personas/*.yaml` — your persona overrides ### What SHIFT Transmits When you enable delegation, the following are sent to whatever model providers you configure for each persona: - Your message content - Conversation history (last N turns, controlled by `contextBridge.historyTurns`) - Active file contents and MEMORY.md excerpts relevant to the task - Delegation metadata (runId, timestamps, persona name) **You control which models are used.** SHIFT does not ship with or store credentials — it uses the model providers configured in your OpenClaw agent config. Review your provider's data handling policy. ### Data Exposure Risk If your workspace files or MEMORY.md contain secrets (API keys, credentials, private data), and those files are referenced in a delegated task, that content will be transmitted to your configured model provider. **Mitigations:** - Do not delegate tasks that reference sensitive file paths - Set `contextBridge.historyTurns` to a low number (e.g., 3) - Use `costManagement.trackOnly: true` during evaluation to observe behavior without enforcement - Use trusted or self-hosted model providers for sensitive work ### Setup Script `scripts/setup.sh` creates local directories only. It does NOT: - Make network calls - Escalate privileges - Modify system files - Access credentials ### Cost and Consultations Consultations spawn additional model calls. Costs are tracked in `cost-tracking.json` per delegation. Set `costManagement.trackOnly: true` to monitor before enforcing limits. ### Recommendations 1. Start with `costManagement.trackOnly: true` to observe costs 2. Set `contextBridge.historyTurns` to a small number (5 or less) 3. Set `contextBridge.archiveAfterMinutes: 30` for faster cleanup 4. Do not delegate tasks referencing sensitive file paths 5. Review model providers' data policies before sensitive work --- Triggers on: any message that might benefit from specialized handling — coding tasks, research, analysis, quick lookups, or anything that warrants delegating to a sub-identity. When SHIFT triggers, you read and follows the procedures below to: classify the task, delegate to the right sub-identity, handle consultation between sub-identities, and synthesize the final response in his own voice. --- # SHIFT Procedures Follow these steps for every message that triggers SHIFT. --- ## STEP 1 — Fast Path Check Before anything, check if this message is trivially handled by you directly. **Bypass delegation (return `none`) if message is ONLY:** - Greetings: `hi`, `hey`, `hello`, `yo`, `sup` - Acknowledgments: `thanks`, `thank you`, `ty`, `ok`, `sure`, `got it`, `makes sense`, `cool`, `nice` - Meta: `that was fast`, `nice one`, `lol`, `haha` **If none of those match, proceed to STEP 2.** --- ## STEP 2 — Load Config Read the SHIFT config at: ``` ~/.openclaw/workspace/.shift/config.yaml ``` If the file doesn't exist, run the setup script first: ```bash bash ~/.openclaw/workspace/skills/shift/scripts/setup.sh ``` From config, extract: - `displayMode` — `hidden` or `transparent` - `fastPath` — `conservative` or `off` - `costManagement.enabled`, `costManagement.costBudgetPerHour`, `costManagement.alertThreshold` - `contextBridge.historyTurns`, `contextBridge.sessionFolder` - `personas` — enabled personas and their settings --- ## STEP 3 — Cost Budget Check If `costManagement.enabled: true`: Read `~/.openclaw/workspace/.shift/cost-tracking.json`: ```json { "hourStart": "2026-03-18T15:00:00Z", "totalSpend": 0.87, "delegations": [...] } ``` **If current UTC hour > hourStart (new hour):** → Reset `totalSpend: 0`, update `hourStart` to current hour. **If `totalSpend >= costBudgetPerHour`:** → You handle the task directly. Say: *"Handling this one myself to stay within your cost budget."* Return `budget_exceeded`. **If `totalSpend >= alertThreshold * costBudgetPerHour`:** → Send a quiet warning: *"Approaching delegation budget limit for this hour."* --- ## STEP 4 — Route to Persona Using the enabled personas from config, classify the user's message. ### Keyword Scoring For each enabled persona, count keyword matches in the user's message (case-insensitive, whole-word). Raw score = matches / total keywords. **If raw score >= `minConfidence`:** Add to candidates. **Runner special case:** Runner has `requireExplicit: true`. It only triggers if the message is predominantly a Runner task, not just containing a keyword. If the message has strong code/research keywords, Runner is NOT a match even if it has Runner keywords. ### Tie-Breaking If multiple personas score above threshold: → Higher score wins. If tied: codex > researcher > runner. ### Default If no persona scores above threshold → You handle directly. Return `none`. --- ## STEP 5 — Prepare Delegation Context Generate a unique `runId`: ``` run-{YYYYMMDD}-{HHMM}-{persona}-{sequence} Example: run-20260318-1551-codex-001 ``` Create the session folder: ``` ~/.openclaw/workspace/.shift/sessions/{runId}/ ``` ### Write INBOUND.json ```json { "runId": "<runId>", "timestamp": "<ISO UTC>", "persona": "<matched persona>", "userMessage": "<exact user message>", "masterConversationHistory": <last N turns from conversation>, "activeFiles": <files mentioned>, "masterSummary": "<brief summary of conversation so far>" } ``` ### Write CONTEXT.md Pull from: - `~/.openclaw/workspace/MEMORY.md` (keyword-matched relevant sections) - Any active file contents mentioned in the conversation - Persona-specific context needs (from the persona definition in config) Format: ```markdown # Context for {persona} ## Project/Memory (relevant) ... ## Active Files ... ## Persona Context Needs ... ``` --- ## STEP 6 — Build Task Prompt Construct the prompt for the sub-agent: ```markdown # You are {persona_name} ## Persona {persona voice, tone, strengths, blind spots from config} ## Your Task {user's exact message} ## Context Before starting, read: - /path/to/INBOUND.json — your input and conversation history - /path/to/CONTEXT.md — relevant project context ## Your Protocol 1. Read INBOUND.json and CONTEXT.md 2. Execute your task 3. If you need to consult another sub-identity and your persona allows it: - Write your question to the session folder as CONSULT-INBOUND.md - Set a timeout: min(remaining_time * 0.5, your consultationTimeout) - Spawn the target sub-identity using sessions_spawn - Wait for them to write CONSULT-OUTBOUND.md - Read their response and continue with that context 4. Write your final result to /path/to/OUTBOUND.md 5. Include a ConsultationLog if you consulted anyone 6. End your response with [DONE] ``` --- ## STEP 7 — Spawn Sub-Agent ```javascript sessions_spawn({ model: personaConfig.model, task: taskPrompt, label: `shift-${persona}-${runId}`, timeoutSeconds: personaConfig.timeout, attachments: [ { name: "INBOUND.json", content: <inboundJsonString> }, { name: "CONTEXT.md", content: <contextMdString> } ] }) ``` **Track elapsed time.** If `elapsed > timeout * 0.7`: → Send status to user: *"{persona} is still working on this..."* --- ## STEP 8 — Wait and Read Result Wait for `sessions_spawn` to complete. ### Read OUTBOUND.md From the session folder: ``` ~/.openclaw/workspace/.shift/sessions/{runId}/OUTBOUND.md ``` Parse: - `Status`: `complete` | `error` | `escalation` - `Result`: the actual response content - `ConsultationLog`: if sub-identity consulted another - `Cost`: token counts if available ### Check for ESCALATE.md (Runner only) If `Status: escalation`: → Runner detected the task was too complex. You take over directly. → Read `reason`, `summary`, `partialAnswer` from ESCALATE.md. → Incorporate any partial work Runner did. --- ## STEP 9 — Update Cost Tracking After successful delegation, update `cost-tracking.json`: ```json { "hourStart": "<current hour UTC>", "totalSpend": <previous + estimated cost>, "delegations": [ { "runId": "<runId>", "persona": "<persona>", "inputTokens": <from sub-agent result if available>, "outputTokens": <from sub-agent result if available>, "estimatedCost": <calculate from model cost config>, "timestamp": "<now>" } ] } ``` --- ## STEP 10 — Synthesize Response Transform the sub-identity's output into your voice. ### Detection If `ConsultationLog` is present and non-empty: → Build consultation mention (ALWAYS shown): ``` {parent persona} consulted {target persona} on {topic}... ``` ### Transformation Rules | Sub-identity output | your transformation | |---|---| | Code | Explain what it does in plain English, highlight key parts, offer to add tests | | Analysis/Research | Pull 2-3 key insights, bullet-point them, note caveats | | Quick answer (Runner) | Relay directly with warmth added | ### Display Mode **Hidden (default):** ``` [Assistant]: Here's the {implementation/analysis/answer}... ``` **Transparent:** ``` [Assistant] → [{persona}] working on this... [Assistant] ← [{persona}] done. [Assistant]: Here's the... ``` Consultation mentions are ALWAYS shown in both modes. --- ## STEP 11 — Handle Errors | Scenario | Response | |---|---| | Sub-agent timeout | *"Looks like this one is taking longer than expected — let me work through it directly."* | | Sub-agent error | *"Hit a snag with the specialist — let me handle this myself."* | | sessions_spawn fails | Fall back to your handling directly | | OUTBOUND.md missing | Assume sub-agent failed, You handle directly | | Model unavailable | Log warning, You handle directly | --- # Consultation Protocol (Master-Orchestrated) **Key insight:** Sub-agent sessions cannot cleanly spawn child sessions and wait. The solution: You orchestrate the consultation from the master level. ## Flow ``` Codex needs context ↓ Codex writes CONSULT-INBOUND.md + OUTBOUND.md (Status: needs_consultation) ↓ You detect needs_consultation flag in OUTBOUND.md ↓ You tell user (transparent mode): "Codex ↔ [Codex → Researcher]..." ↓ You spawn Researcher with CONSULT-INBOUND.md ↓ Researcher writes CONSULT-OUTBOUND.md ↓ You read it, appends to Codex's CONTEXT.md ↓ You re-spawn Codex with enriched context (brief task: "continue with this context") ↓ Codex writes final OUTBOUND.md with ConsultationLog ↓ You synthesize — mentions the consultation (always visible) ``` ## Sub-Agent Side (Codex/Researcher) When a sub-agent needs to consult another sub-identity: 1. Check: is target in my `consults` list? Is target NOT in my `consultsNever`? 2. Write `CONSULT-INBOUND.md` to the session folder with the question + context 3. Write `OUTBOUND.md` with: ```markdown ## Status: needs_consultation ## PartialResult (what Codex has done/understood so far) ## ConsultationLog - consulted: researcher - question: "..." - status: pending ``` 4. End response with `[NEEDS_CONSULTATION]` instead of `[DONE]` 5. Stop — You will take over from here ## Master Side When reading OUTBOUND.md after a sub-agent returns: ### STEP 8a — Detect Consultation Need If `Status: needs_consultation` is present: 1. Read `ConsultationLog` to get target and question 2. Read `CONSULT-INBOUND.md` for full context 3. Send user update (transparent mode): `[Assistant] ↔ [{persona} → {target}] consulting on {topic}...` 4. Proceed to STEP 8b ### STEP 8b — Run Consultation ```javascript // Spawn the target sub-identity as a one-shot consultation sessions_spawn({ model: targetPersonaConfig.model, task: `You are ${target}. Read the consultation question from: <path to CONSULT-INBOUND.md> Write your answer to: <path to CONSULT-OUTBOUND.md> End with [DONE].`, label: `shift-consult-${runId}`, timeoutSeconds: targetPersonaConfig.consultationTimeout }) ``` ### STEP 8c — Feed Result Back After consultation completes: 1. Read `CONSULT-OUTBOUND.md` 2. Append consultation answer to `CONTEXT.md`: ```markdown ## Consultation Answer from {target} {answer from CONSULT-OUTBOUND.md} ``` 3. Re-spawn the original sub-agent with enriched context: ```javascript sessions_spawn({ model: originalPersonaConfig.model, task: `${originalPersonaPrompt} ## Additional Context (from consultation) The ${target} provided the following guidance: <answer from CONSULT-OUTBOUND.md> Continue your task using this context. Write your final result to OUTBOUND.md. End with [DONE].`, label: `shift-${originalPersona}-consult-continue-${runId}`, timeoutSeconds: originalPersonaConfig.timeout / 2 // Half remaining time }) ``` ### STEP 8d — Final Result When re-spawned sub-agent completes: 1. Read final `OUTBOUND.md`
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