build: Fixed some model settings
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@@ -8,7 +8,7 @@ description: >
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mode: subagent
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hidden: true
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temperature: 0.1
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model: anthropic/claude-haiku-4-6
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model: anthropic/claude-haiku-4-5
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color: info
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permission:
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edit: deny
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@@ -1,160 +0,0 @@
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# New Escalation Architecture Proposal
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## Overview
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This proposal redesigns the escalation system to eliminate redundancy by leveraging the fact that when a model isn't specified, the agent inherits the model of its caller.
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## Current Problem
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We have massive duplication:
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- `implementer-haiku.md`, `implementer-codex.md`, `implementer-sonnet.md`, `implementer-opus.md`
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- `behave-tester-haiku.md`, `behave-tester-codex.md`, `behave-tester-sonnet.md`, `behave-tester-opus.md`
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- `robot-tester-haiku.md`, `robot-tester-codex.md`, `robot-tester-sonnet.md`, `robot-tester-opus.md`
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Each contains 90% identical content with only the model and escalation context differing.
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## Proposed Solution
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### 1. Core Worker Agents (No Model Specified)
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Create model-agnostic worker agents that contain the actual implementation logic:
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```yaml
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# implementer.md
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---
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description: >
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Core implementation worker that writes code for subtasks. Model is inherited
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from the calling tier agent, enabling progressive escalation without duplication.
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mode: subagent
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hidden: true
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temperature: 0.2
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# NO MODEL SPECIFIED - inherits from caller
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permission:
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edit: allow
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bash:
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"*": allow
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# Block ALL commands that could hit the label creation endpoints
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"*api/v1/orgs/*/labels*": deny
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"*api/v1/repos/*/labels*": deny
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"*https://git.cleverthis.com/api/v1/repos/cleveragents/cleveragents-core/labels*": deny
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task:
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"*": deny
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"ref-reader": allow
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forgejo:
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"*": allow
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# CRITICAL: Label creation is COMPLETELY FORBIDDEN
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"forgejo_create_label": deny
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"forgejo_create_org_label": deny
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"forgejo_create_repo_label": deny
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"forgejo_add_issue_labels": deny
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---
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# [Full implementation logic here - identical for all tiers]
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```
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### 2. Tier Selector Agents
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Create thin wrapper agents that only set the model and invoke the worker:
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```yaml
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# tier-haiku.md
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---
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description: >
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Haiku tier selector for progressive escalation. Sets model to Haiku and
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invokes the requested worker agent.
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mode: subagent
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hidden: true
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temperature: 0.0
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model: anthropic/claude-haiku-4-6
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permission:
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task:
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"implementer": allow
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"behave-tester": allow
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"robot-tester": allow
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"unit-test-runner": allow
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"typecheck-fixer": allow
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---
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# Tier Selector: Haiku
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You are a tier selector that enables Haiku model usage for worker agents.
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When invoked with a worker type and context, immediately invoke that worker
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with the provided context. Your Haiku model will be inherited by the worker.
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## Workers you can invoke:
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- `implementer` - Code implementation
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- `behave-tester` - Unit test writing
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- `robot-tester` - Integration test writing
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- `unit-test-runner` - Unit test execution and fixing
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- `typecheck-fixer` - Type error resolution
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Pass ALL provided context directly to the worker without modification.
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```
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### 3. Updated Subtask Loop
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The subtask-loop agent would be updated to call tier selectors:
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```python
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# Instead of:
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invoke implementer-{tier}
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# Now:
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invoke tier-{tier} with:
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worker_type: "implementer"
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context: {all the implementation context}
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```
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### 4. Benefits
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1. **Eliminates redundancy** - One implementation per worker type
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2. **Easier maintenance** - Update logic in one place
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3. **Cleaner architecture** - Separation of concerns
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4. **Flexible escalation** - Easy to add new tiers or workers
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5. **Consistent behavior** - All tiers guaranteed to use identical logic
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### 5. Migration Path
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Phase 1: Create new architecture
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- Create core worker agents (implementer.md, behave-tester.md, etc.)
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- Create tier selector agents (tier-haiku.md, tier-codex.md, etc.)
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- Update subtask-loop.md to use new pattern
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Phase 2: Testing
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- Test with one worker type first (e.g., implementer)
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- Verify escalation works correctly
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- Ensure state persistence still functions
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Phase 3: Full rollout
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- Migrate all worker types
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- Delete old tier-specific agents
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- Update any other agents that reference them
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### 6. State Persistence
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The escalation state tracking remains in subtask-loop and other orchestrators.
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The tier selectors are stateless - they just set the model and pass through.
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### 7. Example Usage
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```
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subtask-loop determines tier="haiku", worker="implementer"
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→ invokes tier-haiku with {worker_type: "implementer", context: {...}}
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→ tier-haiku (model: haiku) invokes implementer with context
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→ implementer (inherits haiku model) does the work
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If that fails, subtask-loop escalates to tier="codex"
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→ invokes tier-codex with {worker_type: "implementer", context: {...}}
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→ tier-codex (model: codex) invokes implementer with context
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→ implementer (inherits codex model) does the work
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```
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## Implementation Order
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1. Start with implementer as proof of concept
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2. Add unit-test-runner and typecheck-fixer (as requested)
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3. Migrate behave-tester and robot-tester
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4. Consider other agents that could benefit (coverage-checker, test-fixer)
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This architecture provides maximum flexibility with minimal redundancy.
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@@ -6,7 +6,7 @@ description: >
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mode: subagent
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hidden: true
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temperature: 0.0
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model: anthropic/claude-haiku-4-6
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model: anthropic/claude-haiku-4-5
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color: info
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permission:
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edit: deny
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@@ -7,7 +7,7 @@ description: >
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mode: subagent
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hidden: true
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temperature: 0.3
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model: anthropic/claude-haiku-4-6
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model: anthropic/claude-haiku-4-5
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color: "#9B59B6"
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permission:
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edit: deny
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@@ -6,7 +6,7 @@ description: >
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mode: subagent
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hidden: true
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temperature: 0.3
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model: anthropic/claude-haiku-4-6
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model: anthropic/claude-haiku-4-5
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color: secondary
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permission:
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edit: deny
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@@ -5,7 +5,7 @@ description: >
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mode: subagent
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hidden: true
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temperature: 0.0
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model: anthropic/claude-haiku-4-6
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model: anthropic/claude-haiku-4-5
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permission:
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task:
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"implementer": allow
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@@ -84,4 +84,4 @@ invoke implementer
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[all other fields exactly as provided]
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```
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The implementer will then execute using the Haiku model inherited from you.
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The implementer will then execute using the Haiku model inherited from you.
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