background: false is the default. Use foreground dispatch whenever the result determines the current answer or next action.
- Use
background: true only for independent work. If this turn must consume a background result, call observe exactly once with action: "wait" and a bounded timeout before continuing; never continue independently while the result is pending.
- Otherwise end the turn and wait for the automatic
teammate-complete notification. Do not rely on SendMessage, team_msg, or hook callbacks as completion signals.
- Never silently ignore an unfinished dispatch.
Skill Tuning
Autonomous diagnosis and optimization for skill execution issues.
Pre-load (before execution)
- Codebase docs: If
.workflow/codebase/ARCHITECTURE.md exists, read for project context
- Specs:
maestro load --type spec --category coding — load coding conventions
- Wiki knowledge:
maestro search "skill design optimization" --json — top 5 entries as prior context
- All optional — proceed without if unavailable
Architecture
┌─────────────────────────────────────────────────────┐
│ Phase 0: Read Specs (mandatory) │
│ → problem-taxonomy.md, tuning-strategies.md │
└─────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────┐
│ Orchestrator (state-driven) │
│ Read state → Select action → Execute → Update → ✓ │
└─────────────────────────────────────────────────────┘
↓ ↓
┌──────────────────────┐ ┌──────────────────┐
│ Diagnosis Phase │ │ Agy CLI │
│ • Context │ │ Deep analysis │
│ • Memory │ │ (on-demand) │
│ • DataFlow │ │ │
│ • Agent │ │ Complex issues │
│ • Docs │ │ Architecture │
│ • Token Usage │ │ Performance │
└──────────────────────┘ └──────────────────┘
↓
┌───────────────────┐
│ Fix & Verify │
│ Apply → Re-test │
└───────────────────┘
Core Issues Detected
| Priority |
Problem |
Root Cause |
Fix Strategy |
| P0 |
Authoring Violation |
Intermediate files, state bloat, file relay |
eliminate_intermediate, minimize_state |
| P1 |
Data Flow Disruption |
Scattered state, inconsistent formats |
state_centralization, schema_enforcement |
| P2 |
Agent Coordination |
Fragile chains, no error handling |
error_wrapping, result_validation |
| P3 |
Context Explosion |
Unbounded history, full content passing |
sliding_window, path_reference |
| P4 |
Long-tail Forgetting |
Early constraint loss |
constraint_injection, checkpoint_restore |
| P5 |
Token Consumption |
Verbose prompts, state bloat |
prompt_compression, lazy_loading |
Problem Categories (Detailed Specs)
See specs/problem-taxonomy.md for:
- Detection patterns (regex/checks)
- Severity calculations
- Impact assessments
Tuning Strategies (Detailed Specs)
See specs/tuning-strategies.md for:
- 10+ strategies per category
- Implementation patterns
- Verification methods
Workflow
| Step |
Action |
Orchestrator Decision |
Output |
| 1 |
action-init |
status='pending' |
Backup, session created |
| 2 |
action-analyze-requirements |
After init |
Required dimensions + coverage |
| 3 |
Diagnosis (6 types) |
Focus areas |
state.diagnosis.{type} |
| 4 |
action-agy-analysis |
Critical issues OR user request |
Deep findings |
| 5 |
action-generate-report |
All diagnosis complete |
state.final_report |
| 6 |
action-propose-fixes |
Issues found |
state.proposed_fixes[] |
| 7 |
action-apply-fix |
Pending fixes |
Applied + verified |
| 8 |
action-complete |
Quality gates pass |
session.status='completed' |
Action Reference
| Category |
Actions |
Purpose |
| Setup |
action-init |
Initialize backup, session state |
| Analysis |
action-analyze-requirements |
Decompose user request via Agy CLI |
| Diagnosis |
action-diagnose-{context,memory,dataflow,agent,docs,token_consumption} |
Detect category-specific issues |
| Deep Analysis |
action-agy-analysis |
Agy CLI: complex/critical issues |
| Reporting |
action-generate-report |
Consolidate findings → final_report |
| Fixing |
action-propose-fixes, action-apply-fix |
Generate + apply fixes |
| Verify |
action-verify |
Re-run diagnosis, check gates |
| Exit |
action-complete, action-abort |
Finalize or rollback |
Full action details: phases/actions/
State Management
Single source of truth: {run_dir}/outputs/skill-tuning-{ts}/state.json
{
"status": "pending|running|completed|failed",
"target_skill": { "name": "...", "path": "..." },
"diagnosis": {
"context": {...},
"memory": {...},
"dataflow": {...},
"agent": {...},
"docs": {...},
"token_consumption": {...}
},
"issues": [{"id":"...", "severity":"...", "category":"...", "strategy":"..."}],
"proposed_fixes": [...],
"applied_fixes": [...],
"quality_gate": "pass|fail",
"final_report": "..."
}
See phases/state-schema.md for complete schema.
Orchestrator Logic
See phases/orchestrator.md for:
- Decision logic (termination checks → action selection)
- State transitions
- Error recovery
Key Principles
- Problem-First: Diagnosis before any fix
- Data-Driven: Record traces, token counts, snapshots
- Iterative: Multiple rounds until quality gates pass
- Reversible: All changes with backup checkpoints
- Non-Invasive: Minimal changes, maximum clarity
Usage Examples
# Basic skill diagnosis
/skill-tuning "Fix memory leaks in my skill"
# Deep analysis with Agy
/skill-tuning "Architecture issues in async workflow"
# Focus on specific areas
/skill-tuning "Optimize token consumption and fix agent coordination"
# Custom issue
/skill-tuning "My skill produces inconsistent outputs"
Output
After completion, review:
{run_dir}/outputs/skill-tuning-{ts}/state.json - Full state with final_report
state.final_report - Markdown summary (in state.json)
state.applied_fixes - List of applied fixes with verification results
Reference Documents
| Document |
Purpose |
| specs/problem-taxonomy.md |
Classification + detection patterns |
| specs/tuning-strategies.md |
Fix implementation guide |
| specs/dimension-mapping.md |
Dimension ↔ Spec mapping |
| specs/quality-gates.md |
Quality verification criteria |
| phases/orchestrator.md |
Workflow orchestration |
| phases/state-schema.md |
State structure definition |
| phases/actions/ |
Individual action implementations |
1---2name: skill-tuning-33description: Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Agy CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".4---56<teammate_contract>78- `background: false` is the default. Use foreground dispatch whenever the result determines the current answer or next action.9- Use `background: true` only for independent work. If this turn must consume a background result, call `observe` exactly once with `action: "wait"` and a bounded timeout before continuing; never continue independently while the result is pending.10- Otherwise end the turn and wait for the automatic `teammate-complete` notification. Do not rely on `SendMessage`, `team_msg`, or hook callbacks as completion signals.11- Never silently ignore an unfinished dispatch.1213</teammate_contract>1415<required_reading>16~/.maestro/workflows/run-mode.md17</required_reading>1819# Skill Tuning2021Autonomous diagnosis and optimization for skill execution issues.2223## Pre-load (before execution)24251. **Codebase docs**: If `.workflow/codebase/ARCHITECTURE.md` exists, read for project context262. **Specs**: `maestro load --type spec --category coding` — load coding conventions273. **Wiki knowledge**: `maestro search "skill design optimization" --json` — top 5 entries as prior context284. All optional — proceed without if unavailable2930## Architecture3132```33┌─────────────────────────────────────────────────────┐34│ Phase 0: Read Specs (mandatory) │35│ → problem-taxonomy.md, tuning-strategies.md │36└─────────────────────────────────────────────────────┘37 ↓38┌─────────────────────────────────────────────────────┐39│ Orchestrator (state-driven) │40│ Read state → Select action → Execute → Update → ✓ │41└─────────────────────────────────────────────────────┘42 ↓ ↓43┌──────────────────────┐ ┌──────────────────┐44│ Diagnosis Phase │ │ Agy CLI │45│ • Context │ │ Deep analysis │46│ • Memory │ │ (on-demand) │47│ • DataFlow │ │ │48│ • Agent │ │ Complex issues │49│ • Docs │ │ Architecture │50│ • Token Usage │ │ Performance │51└──────────────────────┘ └──────────────────┘52 ↓53 ┌───────────────────┐54 │ Fix & Verify │55 │ Apply → Re-test │56 └───────────────────┘57```5859## Core Issues Detected6061| Priority | Problem | Root Cause | Fix Strategy |62|----------|---------|-----------|--------------|63| **P0** | Authoring Violation | Intermediate files, state bloat, file relay | eliminate_intermediate, minimize_state |64| **P1** | Data Flow Disruption | Scattered state, inconsistent formats | state_centralization, schema_enforcement |65| **P2** | Agent Coordination | Fragile chains, no error handling | error_wrapping, result_validation |66| **P3** | Context Explosion | Unbounded history, full content passing | sliding_window, path_reference |67| **P4** | Long-tail Forgetting | Early constraint loss | constraint_injection, checkpoint_restore |68| **P5** | Token Consumption | Verbose prompts, state bloat | prompt_compression, lazy_loading |6970## Problem Categories (Detailed Specs)7172See [specs/problem-taxonomy.md](specs/problem-taxonomy.md) for:73- Detection patterns (regex/checks)74- Severity calculations75- Impact assessments7677## Tuning Strategies (Detailed Specs)7879See [specs/tuning-strategies.md](specs/tuning-strategies.md) for:80- 10+ strategies per category81- Implementation patterns82- Verification methods8384## Workflow8586| Step | Action | Orchestrator Decision | Output |87|------|--------|----------------------|--------|88| 1 | `action-init` | status='pending' | Backup, session created |89| 2 | `action-analyze-requirements` | After init | Required dimensions + coverage |90| 3 | Diagnosis (6 types) | Focus areas | state.diagnosis.{type} |91| 4 | `action-agy-analysis` | Critical issues OR user request | Deep findings |92| 5 | `action-generate-report` | All diagnosis complete | state.final_report |93| 6 | `action-propose-fixes` | Issues found | state.proposed_fixes[] |94| 7 | `action-apply-fix` | Pending fixes | Applied + verified |95| 8 | `action-complete` | Quality gates pass | session.status='completed' |9697## Action Reference9899| Category | Actions | Purpose |100|----------|---------|---------|101| **Setup** | action-init | Initialize backup, session state |102| **Analysis** | action-analyze-requirements | Decompose user request via Agy CLI |103| **Diagnosis** | action-diagnose-{context,memory,dataflow,agent,docs,token_consumption} | Detect category-specific issues |104| **Deep Analysis** | action-agy-analysis | Agy CLI: complex/critical issues |105| **Reporting** | action-generate-report | Consolidate findings → final_report |106| **Fixing** | action-propose-fixes, action-apply-fix | Generate + apply fixes |107| **Verify** | action-verify | Re-run diagnosis, check gates |108| **Exit** | action-complete, action-abort | Finalize or rollback |109110Full action details: [phases/actions/](phases/actions/)111112## State Management113114**Single source of truth**: `{run_dir}/outputs/skill-tuning-{ts}/state.json`115116```json117{118 "status": "pending|running|completed|failed",119 "target_skill": { "name": "...", "path": "..." },120 "diagnosis": {121 "context": {...},122 "memory": {...},123 "dataflow": {...},124 "agent": {...},125 "docs": {...},126 "token_consumption": {...}127 },128 "issues": [{"id":"...", "severity":"...", "category":"...", "strategy":"..."}],129 "proposed_fixes": [...],130 "applied_fixes": [...],131 "quality_gate": "pass|fail",132 "final_report": "..."133}134```135136See [phases/state-schema.md](phases/state-schema.md) for complete schema.137138## Orchestrator Logic139140See [phases/orchestrator.md](phases/orchestrator.md) for:141- Decision logic (termination checks → action selection)142- State transitions143- Error recovery144145## Key Principles1461471. **Problem-First**: Diagnosis before any fix1482. **Data-Driven**: Record traces, token counts, snapshots1493. **Iterative**: Multiple rounds until quality gates pass1504. **Reversible**: All changes with backup checkpoints1515. **Non-Invasive**: Minimal changes, maximum clarity152153## Usage Examples154155```bash156# Basic skill diagnosis157/skill-tuning "Fix memory leaks in my skill"158159# Deep analysis with Agy160/skill-tuning "Architecture issues in async workflow"161162# Focus on specific areas163/skill-tuning "Optimize token consumption and fix agent coordination"164165# Custom issue166/skill-tuning "My skill produces inconsistent outputs"167```168169## Output170171After completion, review:172- `{run_dir}/outputs/skill-tuning-{ts}/state.json` - Full state with final_report173- `state.final_report` - Markdown summary (in state.json)174- `state.applied_fixes` - List of applied fixes with verification results175176## Reference Documents177178| Document | Purpose |179|----------|---------|180| [specs/problem-taxonomy.md](specs/problem-taxonomy.md) | Classification + detection patterns |181| [specs/tuning-strategies.md](specs/tuning-strategies.md) | Fix implementation guide |182| [specs/dimension-mapping.md](specs/dimension-mapping.md) | Dimension ↔ Spec mapping |183| [specs/quality-gates.md](specs/quality-gates.md) | Quality verification criteria |184| [phases/orchestrator.md](phases/orchestrator.md) | Workflow orchestration |185| [phases/state-schema.md](phases/state-schema.md) | State structure definition |186| [phases/actions/](phases/actions/) | Individual action implementations |