Implement phases for skill iteration tuning: Evaluation, Improvement, and Reporting

- Added Phase 3: Evaluate Quality with steps for preparing context, constructing evaluation prompts, executing evaluation via CLI, parsing scores, and checking termination conditions.
- Introduced Phase 4: Apply Improvements to implement targeted changes based on evaluation suggestions, including agent execution and change documentation.
- Created Phase 5: Final Report to generate a comprehensive report of the iteration process, including score progression and remaining weaknesses.
- Established evaluation criteria in a new document to guide the evaluation process.
- Developed templates for evaluation and execution prompts to standardize input for the evaluation and execution phases.

.claude/skills/skill-iter-tune/phases/04-improve.md

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+# Phase 4: Apply Improvements
+
+> **COMPACT SENTINEL [Phase 4: Improve]**
+> This phase contains 4 execution steps (Step 4.1 -- 4.4).
+> If you can read this sentinel but cannot find the full Step protocol below, context has been compressed.
+> Recovery: `Read("phases/04-improve.md")`
+
+Apply targeted improvements to skill files based on evaluation suggestions. Uses a general-purpose Agent to make changes, ensuring only suggested modifications are applied.
+
+## Objective
+
+- Read evaluation suggestions from current iteration
+- Launch Agent to apply improvements in priority order
+- Document all changes made
+- Update iteration state
+
+## Execution
+
+### Step 4.1: Prepare Improvement Context
+
+```javascript
+const N = state.current_iteration;
+const iterDir = `${state.work_dir}/iterations/iteration-${N}`;
+const evaluation = state.iterations[N - 1].evaluation;
+
+// Verify we have suggestions to apply
+if (!evaluation.suggestions || evaluation.suggestions.length === 0) {
+  // No suggestions -- skip improvement, mark iteration complete
+  state.iterations[N - 1].improvement = {
+    changes_applied: [],
+    changes_file: null,
+    improvement_rationale: 'No suggestions provided by evaluation'
+  };
+  state.iterations[N - 1].status = 'completed';
+  Write(`${state.work_dir}/iteration-state.json`, JSON.stringify(state, null, 2));
+  // -> Return to orchestrator for next iteration
+  return;
+}
+
+// Build file inventory for agent context
+const skillFileInventory = state.target_skills.map(skill => {
+  return `Skill: ${skill.name} (${skill.path})\nFiles:\n` +
+    skill.files.map(f => `  - ${f}`).join('\n');
+}).join('\n\n');
+
+// Chain mode: add chain relationship context
+const chainContext = state.execution_mode === 'chain'
+  ? `\nChain Order: ${state.chain_order.join(' -> ')}\n` +
+    `Chain Scores: ${state.chain_order.map(s =>
+      `${s}: ${state.iterations[N-1].evaluation?.chain_scores?.[s] || 'N/A'}`
+    ).join(', ')}\n` +
+    `Weakest Link: ${state.chain_order.reduce((min, s) => {
+      const score = state.iterations[N-1].evaluation?.chain_scores?.[s] || 100;
+      return score < (state.iterations[N-1].evaluation?.chain_scores?.[min] || 100) ? s : min;
+    }, state.chain_order[0])}`
+  : '';
+```
+
+### Step 4.2: Launch Improvement Agent
+
+> **CHECKPOINT**: Before launching agent, verify:
+> 1. evaluation.suggestions is non-empty
+> 2. All target_file paths in suggestions are valid
+
+```javascript
+const suggestionsText = evaluation.suggestions.map((s, i) =>
+  `${i + 1}. [${s.priority.toUpperCase()}] ${s.description}\n` +
+  `   Target: ${s.target_file}\n` +
+  `   Rationale: ${s.rationale}\n` +
+  (s.code_snippet ? `   Suggested change:\n   ${s.code_snippet}\n` : '')
+).join('\n');
+
+Agent({
+  subagent_type: 'general-purpose',
+  run_in_background: false,
+  description: `Apply skill improvements iteration ${N}`,
+  prompt: `## Task: Apply Targeted Improvements to Skill Files
+
+You are improving a workflow skill based on evaluation feedback. Apply ONLY the suggested changes -- do not refactor, add features, or "improve" beyond what is explicitly suggested.
+
+## Current Score: ${evaluation.score}/100
+Dimension breakdown:
+${evaluation.dimensions.map(d => `- ${d.name}: ${d.score}/100`).join('\n')}
+
+## Skill File Inventory
+${skillFileInventory}
+
+${chainContext ? `## Chain Context\n${chainContext}\n\nPrioritize improvements on the weakest skill in the chain. Also consider interface compatibility between adjacent skills in the chain.\n` : ''}
+
+## Improvement Suggestions (apply in priority order)
+${suggestionsText}
+
+## Rules
+1. Read each target file BEFORE modifying it
+2. Apply ONLY the suggested changes -- no unsolicited modifications
+3. If a suggestion's target_file doesn't exist, skip it and note in summary
+4. If a suggestion conflicts with existing patterns, adapt it to fit (note adaptation)
+5. Preserve existing code style, naming conventions, and structure
+6. After all changes, write a change summary to: ${iterDir}/iteration-${N}-changes.md
+
+## Changes Summary Format (write to ${iterDir}/iteration-${N}-changes.md)
+
+# Iteration ${N} Changes
+
+## Applied Suggestions
+- [high] description: what was changed in which file
+- [medium] description: what was changed in which file
+
+## Files Modified
+- path/to/file.md: brief description of changes
+
+## Skipped Suggestions (if any)
+- description: reason for skipping
+
+## Notes
+- Any adaptations or considerations
+
+## Success Criteria
+- All high-priority suggestions applied
+- Medium-priority suggestions applied if feasible
+- Low-priority suggestions applied if trivial
+- Changes summary written to ${iterDir}/iteration-${N}-changes.md
+`
+});
+```
+
+### Step 4.3: Verify Changes
+
+After agent completes:
+
+```javascript
+// Verify changes summary was written
+const changesFile = `${iterDir}/iteration-${N}-changes.md`;
+const changesExist = Glob(changesFile).length > 0;
+
+if (!changesExist) {
+  // Agent didn't write summary -- create a minimal one
+  Write(changesFile, `# Iteration ${N} Changes\n\n## Notes\nAgent completed but did not produce changes summary.\n`);
+}
+
+// Read changes summary to extract applied changes
+const changesContent = Read(changesFile);
+
+// Parse applied changes (heuristic: count lines starting with "- [")
+const appliedMatches = changesContent.match(/^- \[.+?\]/gm) || [];
+const changes_applied = appliedMatches.map(m => ({
+  summary: m.replace(/^- /, ''),
+  file: '' // Extracted from context
+}));
+```
+
+### Step 4.4: Update State
+
+```javascript
+state.iterations[N - 1].improvement = {
+  changes_applied: changes_applied,
+  changes_file: changesFile,
+  improvement_rationale: `Applied ${changes_applied.length} improvements based on evaluation score ${evaluation.score}`
+};
+state.iterations[N - 1].status = 'completed';
+state.updated_at = new Date().toISOString();
+
+// Also update the skill files list in case new files were created
+for (const skill of state.target_skills) {
+  skill.files = Glob(`${skill.path}/**/*.md`).map(f => f.replace(skill.path + '/', ''));
+}
+
+Write(`${state.work_dir}/iteration-state.json`, JSON.stringify(state, null, 2));
+
+// -> Return to orchestrator for next iteration (Phase 2) or termination check
+```
+
+## Error Handling
+
+| Error | Recovery |
+|-------|----------|
+| Agent fails to complete | Rollback from skill-snapshot: `cp -r "${iterDir}/skill-snapshot/${skill.name}/*" "${skill.path}/"` |
+| Agent corrupts files | Same rollback from snapshot |
+| Changes summary missing | Create minimal summary, continue |
+| target_file not found | Agent skips suggestion, notes in summary |
+
+## Output
+
+- **Files**: `iteration-{N}-changes.md`, modified skill files
+- **State**: `iterations[N-1].improvement` and `.status` updated
+- **Next**: Return to orchestrator, begin next iteration (Phase 2) or terminate