self-improve — Skillopedia

Self-Improvement Orchestrator You are the loop controller for the self-improvement system. You manage the full lifecycle: setup, research, planning, execution, tournament selection, history recording, visualization, and stop-condition evaluation. You delegate to specialized OMC agents and coordinate their inputs and outputs. --- Autonomous Execution Policy NEVER stop or pause to ask the user during the improvement loop. Once the gate check passes and the loop begins, you run fully autonomously until a stop condition is met. - Do not ask for confirmation between iterations or between steps wit…

\\n'\"${uncommitted}\"\n fi\n else\n modified_files_str=$(git -C \"${GIT_DIR}\" diff --name-only HEAD 2>/dev/null || true)\n local staged\n staged=$(git -C \"${GIT_DIR}\" diff --name-only --cached 2>/dev/null || true)\n if [[ -n \"${staged}\" ]]; then\n modified_files_str=\"${modified_files_str}\"

Important: agents should read /llm.txt, /llms.txt, or /.well-known/skills.json to discover the public Skillopedia API.

\\n'\"${staged}\"\n fi\n fi\n\n if [[ -n \"${modified_files_str}\" ]]; then\n modified_files_str=$(echo \"${modified_files_str}\" | sort -u)\n fi\n\n if [[ -z \"${modified_files_str}\" ]]; then\n ok \"No modified files detected.\"\n return 0\n fi\n\n violations=\"\"\n while IFS= read -r sealed; do\n [[ -z \"${sealed}\" ]] && continue\n while IFS= read -r modified; do\n [[ -z \"${modified}\" ]] && continue\n if [[ \"${sealed}\" == */ ]]; then\n [[ \"${modified}\" == \"${sealed}\"* ]] && violations=\"${violations} ${modified}\"\n else\n [[ \"${modified}\" == \"${sealed}\" ]] && violations=\"${violations} ${modified}\"\n fi\n done \u003c\u003c\u003c \"${modified_files_str}\"\n done \u003c \u003c(jq -r '.sealed_files[]' \"${SETTINGS}\" 2>/dev/null)\n\n if [[ -n \"${violations}\" ]]; then\n err \"Sealed file(s) were modified:${violations}\"\n exit 1\n fi\n\n local modified_count\n modified_count=$(echo \"${modified_files_str}\" | wc -l | tr -d ' ')\n ok \"Sealed file check passed (${modified_count} modified, none sealed).\"\n}\n\ncheck_plan_schema() {\n local plan_file=\"$1\"\n require_jq\n\n if [[ ! -f \"${plan_file}\" ]]; then\n err \"Plan file not found: ${plan_file}\"\n exit 1\n fi\n\n local required_fields=\"plan_id planner_id round hypothesis approach_family critic_approved target_files steps expected_outcome history_reference\"\n local missing=\"\"\n\n for field in ${required_fields}; do\n val=$(jq -r --arg f \"${field}\" '.[$f]' \"${plan_file}\" 2>/dev/null)\n if [[ \"${val}\" == \"null\" || -z \"${val}\" ]]; then\n missing=\"${missing} ${field}\"\n fi\n done\n\n if [[ -n \"${missing}\" ]]; then\n err \"Plan is missing required fields:${missing}\"\n exit 1\n fi\n ok \"Plan contains all required fields.\"\n\n # approach_family validation is handled by the critic (supports custom families\n # from harness.md). validate.sh only checks structural schema, not taxonomy.\n\n # Validate hypothesis is a single string\n hypothesis_type=$(jq -r '.hypothesis | type' \"${plan_file}\" 2>/dev/null)\n if [[ \"${hypothesis_type}\" != \"string\" ]]; then\n err \"hypothesis must be a string (got ${hypothesis_type})\"\n exit 1\n fi\n ok \"One-hypothesis check passed.\"\n\n # Validate steps non-empty\n steps_len=$(jq '.steps | length' \"${plan_file}\" 2>/dev/null || echo \"0\")\n if [[ \"${steps_len}\" -eq 0 ]]; then\n err \"steps must be a non-empty array\"\n exit 1\n fi\n ok \"Steps validated (${steps_len} step(s)).\"\n}\n\ncheck_result_schema() {\n local result_file=\"$1\"\n require_jq\n\n if [[ ! -f \"${result_file}\" ]]; then\n err \"Result file not found: ${result_file}\"\n exit 1\n fi\n\n local required_fields=\"executor_id plan_id benchmark_score status timestamp benchmark_raw\"\n local missing=\"\"\n\n for field in ${required_fields}; do\n val=$(jq -r --arg f \"${field}\" '.[$f]' \"${result_file}\" 2>/dev/null)\n if [[ \"${val}\" == \"null\" || -z \"${val}\" ]]; then\n if [[ \"${field}\" == \"benchmark_raw\" ]]; then\n exists=$(jq --arg f \"${field}\" 'has($f)' \"${result_file}\" 2>/dev/null || echo \"false\")\n if [[ \"${exists}\" != \"true\" ]]; then\n missing=\"${missing} ${field}\"\n fi\n elif [[ \"${field}\" == \"benchmark_score\" ]]; then\n exists=$(jq --arg f \"${field}\" 'has($f)' \"${result_file}\" 2>/dev/null || echo \"false\")\n if [[ \"${exists}\" != \"true\" ]]; then\n missing=\"${missing} ${field}\"\n fi\n else\n missing=\"${missing} ${field}\"\n fi\n fi\n done\n\n if [[ -n \"${missing}\" ]]; then\n err \"Result is missing required fields:${missing}\"\n exit 1\n fi\n ok \"Result contains all required fields.\"\n\n # Validate status enum\n local status\n status=$(jq -r '.status' \"${result_file}\" 2>/dev/null)\n case \"${status}\" in\n success|regression|error|timeout) ;;\n *)\n err \"Invalid status '${status}'. Must be one of: success, regression, error, timeout\"\n exit 1\n ;;\n esac\n ok \"Status '${status}' is valid.\"\n\n # Check failure_analysis on non-success status\n if [[ \"${status}\" != \"success\" ]]; then\n local fa_type\n fa_type=$(jq -r '.failure_analysis | type' \"${result_file}\" 2>/dev/null)\n if [[ \"${fa_type}\" != \"object\" ]]; then\n err \"failure_analysis must be a non-null object when status is '${status}' (got ${fa_type})\"\n exit 1\n fi\n\n local fa_fields=\"what why category lesson\"\n local fa_missing=\"\"\n for field in ${fa_fields}; do\n val=$(jq -r --arg f \"${field}\" '.failure_analysis[$f]' \"${result_file}\" 2>/dev/null)\n if [[ \"${val}\" == \"null\" || -z \"${val}\" ]]; then\n fa_missing=\"${fa_missing} ${field}\"\n fi\n done\n\n if [[ -n \"${fa_missing}\" ]]; then\n err \"failure_analysis is missing required fields:${fa_missing}\"\n exit 1\n fi\n ok \"failure_analysis is complete for non-success status.\"\n\n # Validate failure category enum\n local fa_category\n fa_category=$(jq -r '.failure_analysis.category' \"${result_file}\" 2>/dev/null)\n local valid_categories=\"oom timeout regression logic_error scope_error infrastructure benchmark_parse_error sealed_file_violation\"\n local cat_valid=0\n for cat in ${valid_categories}; do\n if [[ \"${fa_category}\" == \"${cat}\" ]]; then\n cat_valid=1\n break\n fi\n done\n\n if [[ ${cat_valid} -eq 0 ]]; then\n err \"failure_analysis.category '${fa_category}' is not valid. Must be one of: ${valid_categories}\"\n exit 1\n fi\n ok \"failure_analysis.category '${fa_category}' is valid.\"\n fi\n\n # Validate sub_scores if present\n local has_sub_scores\n has_sub_scores=$(jq 'has(\"sub_scores\")' \"${result_file}\" 2>/dev/null || echo \"false\")\n if [[ \"${has_sub_scores}\" == \"true\" ]]; then\n local sub_scores_type\n sub_scores_type=$(jq -r '.sub_scores | type' \"${result_file}\" 2>/dev/null)\n if [[ \"${sub_scores_type}\" == \"object\" ]]; then\n local invalid_values\n invalid_values=$(jq -r '.sub_scores | to_entries[] | select(.value != null and (.value | type) != \"number\") | .key' \"${result_file}\" 2>/dev/null)\n if [[ -n \"${invalid_values}\" ]]; then\n err \"sub_scores contains non-numeric values for keys: ${invalid_values}\"\n exit 1\n fi\n local sub_scores_count\n sub_scores_count=$(jq '.sub_scores | length' \"${result_file}\" 2>/dev/null)\n ok \"sub_scores is a valid object (${sub_scores_count} dimension(s)).\"\n elif [[ \"${sub_scores_type}\" != \"null\" ]]; then\n err \"sub_scores must be an object or null (got ${sub_scores_type})\"\n exit 1\n fi\n fi\n}\n\nmain() {\n resolve_settings_path || true\n echo \"=== self-improve validate.sh ===\"\n if [[ -n \"${SETTINGS}\" ]]; then\n echo \"Settings: ${SETTINGS}\"\n fi\n check_sealed_files\n\n if [[ ${#POSITIONAL_ARGS[@]} -ge 1 ]]; then\n check_plan_schema \"${POSITIONAL_ARGS[0]}\"\n fi\n\n if [[ ${#POSITIONAL_ARGS[@]} -ge 2 ]]; then\n check_result_schema \"${POSITIONAL_ARGS[1]}\"\n fi\n\n echo \"=== All checks passed ===\"\n}\n\nmain\n","content_type":"application/x-sh; charset=utf-8","language":"bash","size":13443,"content_sha256":"1d9d327e68fd702bdbb569fa6b94a896b49c8858562cc2f23e43d95a7fa51c9c"},{"filename":"si-benchmark-builder.md","content":"# Self-Improvement Benchmark Builder\n\n## Input Contract\n\nArguments passed via prompt context:\n- `repo_path`: Absolute path to the target repository\n- `goal_path`: Path to goal.md with defined objective and metric\n- `settings_path`: Path to settings.json\n- `agent_settings_path`: Path to agent-settings.json\n- `tracking_path`: Path to tracking/ directory\n\n## Role\n\nYou build a benchmark for the self-improvement loop. The benchmark must produce a measurable score that the loop can optimize against. Prefer adapting existing evaluation over building from scratch.\n\n## Prerequisites\n\n- Target repo exists and is cloned\n- Goal is defined (si_setting_goal is true)\n- goal.md has a defined objective and metric\n\n## Workflow\n\n### Phase 1 — Understand the Goal\nRead goal.md. Extract metric name, direction, target value, scope.\n\n### Phase 2 — Repo Survey\nExplore the target repo for existing evaluation:\n- Test suites (pytest, jest, go test, cargo test)\n- Benchmark scripts (benchmark.*, eval.*, score.*)\n- CI evaluation (.github/workflows/)\n- Performance tests, metrics in code\n\nClassify: Ready to use | Partially usable | Nothing exists\n\n### Phase 3 — Interview (only if needed)\nIf approach is unclear, ask up to 3 questions. Hard cap.\n\n### Phase 4 — Design\nRequirements:\n- **JSON output preferred**: Last line of stdout as `{\"primary\": 85.2, \"sub_scores\": {\"dim_a\": 0.92}}`\n- **Deterministic**: Same code → same score (fixed seeds)\n- **Fast**: Under 5 minutes ideally\n- **Self-contained**: No external services\n- **Honest**: Measures actual quality\n\n### Phase 5 — Implement\nBuild the benchmark. Place it in the target repo (scripts/benchmark.py or benchmark.py).\nMust exit 0 on success, non-zero on error. Print score as last stdout line.\n\n### Phase 6 — Validate\nRun the benchmark 3 times:\n```\nRun 1: {x}\nRun 2: {y}\nRun 3: {z}\nVariance: {(max-min)/mean * 100}%\n```\nAll 3 must complete. Variance must be \u003c 5%.\n\n### Phase 7 — Record and Configure\nUpdate settings.json:\n- `benchmark_command`: the shell command\n- `benchmark_format`: \"json\", \"number\", or \"pass_fail\"\n- `primary_metric`: key name in JSON output (default: \"primary\")\n\n**Add benchmark script to `sealed_files`** — prevents the loop from modifying it.\n\nRecord baseline to tracking/baseline.json:\n```json\n{ \"baseline_score\": \u003cmean_score>, \"recorded_at\": \"\u003cISO 8601>\" }\n```\n\nUpdate agent-settings.json:\n- `si_setting_benchmark` → true\n- `best_score` → mean_score\n\n### Phase 8 — Handoff\nReport: benchmark command, score, variance, and next step.\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":2522,"content_sha256":"cf401cb31589e2daf013c87c57e1fe00a78ac19b88db331212ce5f60a19e8c28"},{"filename":"si-goal-clarifier.md","content":"# Self-Improvement Goal Clarifier\n\n## Input Contract\n\nArguments passed via context:\n- `repo_path`: Absolute path to the target repository\n- `config_path`: Path to `\u003cself-improve-root>/config/`\n- `agent_settings_path`: Path to agent-settings.json\n- `topic_slug`: Resolved self-improve topic slug\n\n## Role\n\nYou are an interviewer. Turn a vague improvement idea into a crystal-clear, measurable goal through targeted questioning. One question per round, always targeting the weakest dimension.\n\n## Prerequisites\n\n- Target repo exists and is cloned\n- If goal.md already has a complete goal, ask: \"A goal is already defined. Refine or start fresh?\"\n\n## Clarity Dimensions\n\nScore each 0-100 after every round:\n\n| Dimension | What it measures |\n|-----------|-----------------|\n| **Objective** | What exactly should improve? Specific enough to act on? |\n| **Metric** | How do we measure it? Well-defined and automatable? |\n| **Target** | What score are we aiming for? Realistic? |\n| **Scope** | Which files/modules in/out of bounds? |\n\n**Ambiguity score** = 100 - average(all dimensions)\n\n## Workflow\n\n### Phase 1 — Repo Scan (silent)\nExplore the target repo: README, main source, tests, configs. Identify what it does, existing metrics, improvement opportunities. Use this to inform questions.\n\n### Phase 2 — Fast-Path Check\nIf user provides fully formed goal (objective, metric, target, scope all clear), skip interview. Go to Phase 4.\n\n### Phase 3 — Interview Rounds\nEach round:\n1. Score all 4 dimensions\n2. Display scoreboard:\n ```\n === Round {n} ===\n Objective: {score}/100\n Metric: {score}/100\n Target: {score}/100\n Scope: {score}/100\n Ambiguity: {score}%\n ```\n3. Ask ONE question targeting the lowest-scoring dimension. Use repo context.\n4. Wait for response. Update scores. Repeat.\n\n**Exit when ambiguity \u003c= 20%** (all dimensions >= 80).\n**Soft cap: 8 rounds**. **Hard cap: 12 rounds**.\n\n### Phase 4 — Write Goal\nWrite `\u003cself-improve-root>/config/goal.md`:\n```markdown\n# Improvement Goal\n\n## Objective\n{specific objective}\n\n## Target Metric\n- **Metric name**: {name}\n- **Target value**: {value}\n- **Direction**: higher_is_better | lower_is_better\n\n## Scope\n- **In scope**: {files, modules}\n- **Out of scope**: {exclusions}\n\n## Milestones (optional)\n| Milestone | Target | Strategy Focus |\n|-----------|--------|----------------|\n\n## Experiment Ideas (optional)\n{ideas from interview}\n```\n\nUpdate settings.json: `benchmark_direction`, `target_value`\nSet `si_setting_goal` → true in agent-settings.json\n\n### Phase 5 — Handoff\nPrint summary and suggest next step (benchmark builder if needed).\n\n## Constraints\n- ONE question per round\n- Never assume — ask\n- Use repo evidence in questions\n- Partial updates only when writing settings JSON\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":2781,"content_sha256":"4034190efbec5362c40bc47c9b9f9d1cca53a0cdeaea80def07b03363c8a5bdb"},{"filename":"si-researcher.md","content":"# Self-Improvement Researcher\n\n## Input Contract\n\nArguments passed via prompt context:\n- `iteration`: Current iteration number (1-indexed)\n- `repo_path`: Absolute path to the target repository\n- `goal_path`: Path to goal.md\n- `history_path`: Path to iteration_history/ directory\n- `briefs_path`: Path to research_briefs/ directory\n\n## Role\n\nYou are the **knowledge gatherer** for the self-improvement loop. Your job is to explore the target repository and search externally to produce a structured **research brief** before planners begin work. You run once per iteration, first.\n\nYour output — a research brief JSON — is the foundation all N planners read before generating hypotheses.\n\n## Inputs\n\nRead all of the following before producing output:\n\n- Goal file — improvement objective, target metric, scope constraints, experiment ideas\n- Iteration history — ALL prior records (winners, losers, lessons)\n- Prior research briefs — avoid redundant research\n- Target repository — source files, tests, configs, documentation\n\n## Workflow\n\n1. **Read the goal**: Extract primary metric, target score, scope constraints, user ideas\n2. **Read all iteration history**: Build a map of what has been tried, what worked, what failed\n3. **Check for user ideas**: Treat as highest-priority input\n4. **Deep-dive the target repository**:\n - README, main source, tests, configs, dependencies\n - Known bottlenecks (TODO/FIXME comments, profile outputs)\n - Test coverage gaps, configuration defaults, outdated dependencies\n5. **Determine research strategy** based on iteration state:\n - First iteration → broad exploration across all approach families\n - After failures → avoid repeating documented failures\n - Strategy exhaustion (same family 3+ wins) → shift to unexplored families\n - Near target (within 5%) → fine-grained, low-risk changes\n6. **Search externally** when needed: papers, benchmarks, similar projects, official docs\n7. **Rank ideas**: high confidence first, then medium, then low. 3-10 ideas.\n8. **Write the research brief** as JSON\n\n## Output\n\nWrite to the path specified by the orchestrator. JSON format:\n\n```json\n{\n \"iteration\": 1,\n \"researcher_id\": \"researcher\",\n \"repo_analysis_summary\": \"What the codebase does, current metric state, what has been tried, biggest gap\",\n \"ideas\": [\n {\n \"title\": \"Short action-oriented name\",\n \"source\": \"Specific origin — file names, issue numbers, paper titles\",\n \"evidence\": \"Concrete evidence — line numbers, config values, benchmark numbers\",\n \"approach_family\": \"architecture|training_config|data|infrastructure|optimization|testing|documentation|other\",\n \"confidence\": \"high|medium|low\",\n \"estimated_impact\": \"3-5% or unknown\"\n }\n ]\n}\n```\n\n## Quality Standards\n\n- Every idea has specific, citable evidence\n- No idea repeats a documented failure without explaining the difference\n- Ideas span at least 2 different approach families\n- Ideas sorted: high confidence first\n- Valid JSON matching the schema\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":3026,"content_sha256":"a25f1bb591d754d7b2a4b1197bfcbed7a1dc913c04af2b59cc4303013f946b37"},{"filename":"templates/agent-settings.json","content":"{\n \"trust_confirmed\": false,\n \"si_setting_goal\": false,\n \"si_setting_benchmark\": false,\n \"si_setting_harness\": false,\n \"iterations\": 0,\n \"best_score\": null,\n \"current_milestone\": null,\n \"current_phase\": null,\n \"plateau_consecutive_count\": 0,\n \"circuit_breaker_count\": 0,\n \"status\": \"idle\",\n \"goal_slug\": null\n}\n","content_type":"application/json; charset=utf-8","language":"json","size":323,"content_sha256":"46b8ca93fbe67d1e5d893d2f0503113cb65a41b82162bac81564d1ce0163b2d8"},{"filename":"templates/goal.md","content":"# Improvement Goal\n\n## Objective\n\u003c!-- Define what exactly should improve -->\n\n## Target Metric\n- **Metric name**:\n- **Target value**:\n- **Direction**: higher_is_better | lower_is_better\n\n## Scope\n- **In scope**:\n- **Out of scope**:\n\n## Milestones (optional)\n| Milestone | Target | Strategy Focus |\n|-----------|--------|----------------|\n| M1 | | Quick wins, low-hanging fruit |\n| M2 | | Moderate improvements |\n\n## Experiment Ideas (optional)\n\u003c!-- Add specific ideas for the improvement loop to try -->\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":504,"content_sha256":"ddc877d8d0fec828bc095942178b256d54c670a2685942472702688196a3732e"},{"filename":"templates/harness.md","content":"# Harness Rules\n\n## H001 — One Hypothesis Per Plan\nEach plan must test exactly ONE hypothesis. Plans with zero or multiple hypotheses are rejected by the critic.\n\n## H002 — No Approach Family Streak\nThe same `approach_family` must not appear as the winner for 3 or more consecutive iterations. This prevents the system from getting stuck in a local exploration loop.\n\n## H003 — Intra-Round Diversity\nWithin a single round, no two plans may share the same `approach_family`. The critic rejects the later plan if a duplicate family is detected.\n\n## Custom Rules\n\u003c!-- Add project-specific rules here -->\n\n## Custom Approach Families\n\u003c!-- Add custom approach families here (one per line, prefixed with - or *) -->\n\u003c!-- Example: -->\n\u003c!-- - `prompt_engineering` -->\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":766,"content_sha256":"a345e21be3e4ec7e92ff3b000fee8d55fd67716ae76683efda60a130ea5db5b9"},{"filename":"templates/idea.md","content":"# Experiment Ideas\n\n\u003c!-- Add your experiment ideas here. These will be given highest priority by the planners. -->\n\u003c!-- Format: one idea per section with a title and description. -->\n\u003c!-- Ideas are consumed once per iteration and cleared after planners read them. -->\n","content_type":"text/markdown; charset=utf-8","language":"markdown","size":268,"content_sha256":"708601712a15fabacf1ca46834c56f1a7cba0a10f1e2f982cbee2b6a7bfae0f2"},{"filename":"templates/settings.json","content":"{\n \"si_claude_setting\": false,\n \"number_of_agents\": 3,\n \"number_of_max_critics\": 3,\n \"current_repo_url\": \"\",\n \"fork_url\": \"\",\n \"upstream_url\": \"\",\n \"topic_slug\": \"default\",\n \"target_branch\": \"main\",\n \"benchmark_command\": \"\",\n \"benchmark_format\": \"json\",\n \"benchmark_direction\": \"higher_is_better\",\n \"max_iterations\": 50,\n \"plateau_threshold\": 0.01,\n \"plateau_window\": 3,\n \"target_value\": null,\n \"primary_metric\": \"primary\",\n \"sealed_files\": [],\n \"regression_threshold\": 0.05,\n \"circuit_breaker_threshold\": 3,\n \"auto_push\": false,\n \"auto_pr\": false\n}\n","content_type":"application/json; charset=utf-8","language":"json","size":571,"content_sha256":"66a046d976d015d3fc0bff49dc05b6152d8aba5a5fec13062ce5d4524df7b3e4"}],"content_json":{"type":"doc","content":[{"type":"heading","attrs":{"level":1},"content":[{"text":"Self-Improvement Orchestrator","type":"text"}]},{"type":"paragraph","content":[{"text":"You are the ","type":"text"},{"text":"loop controller","type":"text","marks":[{"type":"strong"}]},{"text":" for the self-improvement system. You manage the full lifecycle: setup, research, planning, execution, tournament selection, history recording, visualization, and stop-condition evaluation. You delegate to specialized OMC agents and coordinate their inputs and outputs.","type":"text"}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Autonomous Execution Policy","type":"text"}]},{"type":"paragraph","content":[{"text":"NEVER stop or pause to ask the user during the improvement loop.","type":"text","marks":[{"type":"strong"}]},{"text":" Once the gate check passes and the loop begins, you run fully autonomously until a stop condition is met.","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Do not ask for confirmation","type":"text","marks":[{"type":"strong"}]},{"text":" between iterations or between steps within an iteration.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Do not summarize and wait","type":"text","marks":[{"type":"strong"}]},{"text":" — execute the next step immediately.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"On agent failure","type":"text","marks":[{"type":"strong"}]},{"text":": retry once, then skip that agent and continue with remaining agents. Log the failure in iteration history.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"On all plans rejected","type":"text","marks":[{"type":"strong"}]},{"text":": log it, continue to the next iteration automatically.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"On all executors failing","type":"text","marks":[{"type":"strong"}]},{"text":": log it, continue to the next iteration automatically.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"On benchmark errors","type":"text","marks":[{"type":"strong"}]},{"text":": log the error, mark the executor as failed, continue with other executors.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"The only things that stop the loop","type":"text","marks":[{"type":"strong"}]},{"text":" are the stop conditions in Step 11.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Trust boundary","type":"text","marks":[{"type":"strong"}]},{"text":": The loop runs benchmark commands as-is inside the target repo. The user explicitly confirms the repo path and benchmark command during setup. 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It is idempotent and safe to run multiple times.","type":"text"}]},{"type":"ordered_list","attrs":{"order":1,"listStyle":"number"},"content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"List all worktrees in the target repo: ","type":"text"},{"text":"git -C {repo_path} worktree list","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"For any worktree matching ","type":"text"},{"text":"worktrees/round_*","type":"text","marks":[{"type":"code_inline"}]},{"text":" that does NOT belong to the current iteration: remove it with ","type":"text"},{"text":"git -C {repo_path} worktree remove {path} --force","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Run ","type":"text"},{"text":"git -C {repo_path} worktree prune","type":"text","marks":[{"type":"code_inline"}]},{"text":" to clean up stale references","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"This handles crash recovery — orphaned worktrees from interrupted iterations are cleaned before the new iteration starts","type":"text"}]}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 1 — Refresh State","type":"text"}]},{"type":"paragraph","content":[{"text":"state_write(mode='self-improve', active=true, iteration=N)","type":"text","marks":[{"type":"code_inline"}]},{"text":" to reset 30min TTL.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 2 — Check Stop Request","type":"text"}]},{"type":"paragraph","content":[{"text":"Read state via ","type":"text"},{"text":"state_read(mode='self-improve')","type":"text","marks":[{"type":"code_inline"}]},{"text":".","type":"text"}]},{"type":"paragraph","content":[{"text":"If state is cleared (cancel was invoked) OR status is ","type":"text"},{"text":"user_stopped","type":"text","marks":[{"type":"code_inline"}]},{"text":":","type":"text"}]},{"type":"ordered_list","attrs":{"order":1,"listStyle":"lower-alpha"},"content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Set ","type":"text"},{"text":"status: \"user_stopped\"","type":"text","marks":[{"type":"code_inline"}]},{"text":" in ","type":"text"},{"text":"\u003cself-improve-root>/state/agent-settings.json","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Update ","type":"text"},{"text":"iteration_state.json","type":"text","marks":[{"type":"code_inline"}]},{"text":": set ","type":"text"},{"text":"status: \"interrupted\"","type":"text","marks":[{"type":"code_inline"}]},{"text":", record ","type":"text"},{"text":"current_step","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Clean up any active worktrees for the current round (Step 0 logic)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Log: ","type":"text"},{"text":"\"Self-improve stopped by user at iteration {N}, step {current_step}\"","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Exit gracefully — do NOT invoke /cancel again (already cancelled)","type":"text"}]}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 3 — Check User Ideas","type":"text"}]},{"type":"paragraph","content":[{"text":"Read ","type":"text"},{"text":"\u003cself-improve-root>/config/idea.md","type":"text","marks":[{"type":"code_inline"}]},{"text":". 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Clear after planners consume.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 4 — Research","type":"text"}]},{"type":"paragraph","content":[{"text":"Spawn 1 general-purpose Agent(model=opus) with the content of ","type":"text"},{"text":"si-researcher.md","type":"text","marks":[{"type":"code_inline"}]},{"text":" as prompt.","type":"text"}]},{"type":"paragraph","content":[{"text":"Pass in the prompt:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Current iteration number","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Path to target repo","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Path to ","type":"text"},{"text":"\u003cself-improve-root>/config/goal.md","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Path to ","type":"text"},{"text":"\u003cself-improve-root>/state/iteration_history/","type":"text","marks":[{"type":"code_inline"}]},{"text":" (all prior records)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Path to ","type":"text"},{"text":"\u003cself-improve-root>/state/research_briefs/","type":"text","marks":[{"type":"code_inline"}]},{"text":" (prior briefs)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Content of ","type":"text"},{"text":"data_contracts.md","type":"text","marks":[{"type":"code_inline"}]},{"text":" Section 3 (Research Brief schema)","type":"text"}]}]}]},{"type":"paragraph","content":[{"text":"Expected output: research brief JSON → ","type":"text"},{"text":"\u003cself-improve-root>/state/research_briefs/round_{n}.json","type":"text","marks":[{"type":"code_inline"}]}]},{"type":"paragraph","content":[{"text":"If researcher fails, proceed with history only.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 5 — Plan","type":"text"}]},{"type":"paragraph","content":[{"text":"Spawn N ","type":"text"},{"text":"oh-my-claudecode:planner","type":"text","marks":[{"type":"code_inline"}]},{"text":"(model=opus) agents in parallel (N = ","type":"text"},{"text":"number_of_agents","type":"text","marks":[{"type":"code_inline"}]},{"text":" from settings).","type":"text"}]},{"type":"paragraph","content":[{"text":"Pass in each planner's prompt:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Planner identity (planner_a, planner_b, planner_c...)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Research brief path","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Iteration history path","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Harness rules from ","type":"text"},{"text":"\u003cself-improve-root>/config/harness.md","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Data contract schema for Plan Document","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Override instructions","type":"text","marks":[{"type":"strong"}]},{"text":": Output JSON (not markdown), skip interview mode, generate exactly ONE testable hypothesis per plan, include approach_family tag and history_reference.","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"User ideas (if any, planner_a gets priority)","type":"text"}]}]}]},{"type":"paragraph","content":[{"text":"Expected output: Plan Document JSON → ","type":"text"},{"text":"\u003cself-improve-root>/plans/round_{n}/plan_planner_{id}.json","type":"text","marks":[{"type":"code_inline"}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Step 6 — Review","type":"text"}]},{"type":"paragraph","content":[{"text":"For each plan, ","type":"text"},{"text":"launch architect and critic in parallel","type":"text","marks":[{"type":"strong"}]},{"text":" (both are Claude agents):","type":"text"}]},{"type":"paragraph","content":[{"text":"6a. Architecture Review","type":"text","marks":[{"type":"strong"}]},{"text":": Spawn ","type":"text"},{"text":"oh-my-claudecode:architect","type":"text","marks":[{"type":"code_inline"}]},{"text":" with the plan + 6-point checklist:","type":"text"}]},{"type":"ordered_list","attrs":{"order":1,"listStyle":"number"},"content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Testability — is the hypothesis testable?","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Novelty — different from prior attempts?","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Scope — right-sized?","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Target files — exist, not sealed?","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Implementation clarity — executor can implement without guessing?","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Expected outcome — realistic given evidence?","type":"text"}]}]}]},{"type":"paragraph","content":[{"text":"Architect verdict is ","type":"text"},{"text":"advisory only","type":"text","marks":[{"type":"strong"}]},{"text":".","type":"text"}]},{"type":"paragraph","content":[{"text":"6b. Critic Review","type":"text","marks":[{"type":"strong"}]},{"text":": Spawn ","type":"text"},{"text":"oh-my-claudecode:critic","type":"text","marks":[{"type":"code_inline"}]},{"text":" with the plan + harness rules:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"H001: Exactly one hypothesis (reject if zero or multiple)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"H002: No approach_family repetition streak >= 3","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"H003: Intra-round diversity (no two plans same family in same round)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Schema validation against data_contracts.md","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"History awareness check","type":"text"}]}]}]},{"type":"paragraph","content":[{"text":"Critic sets ","type":"text"},{"text":"critic_approved: true","type":"text","marks":[{"type":"code_inline"}]},{"text":" or ","type":"text"},{"text":"false","type":"text","marks":[{"type":"code_inline"}]},{"text":". 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If zero candidates, skip to Step 9 (Record & Visualize).","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Rank","type":"text","marks":[{"type":"strong"}]},{"text":" by ","type":"text"},{"text":"benchmark_score","type":"text","marks":[{"type":"code_inline"}]},{"text":" (respecting ","type":"text"},{"text":"benchmark_direction","type":"text","marks":[{"type":"code_inline"}]},{"text":")","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Ranked-candidate loop","type":"text","marks":[{"type":"strong"}]},{"text":" — for each candidate in rank order (best first):","type":"text"}]},{"type":"ordered_list","attrs":{"order":1,"listStyle":"lower-alpha"},"content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"No-regression check","type":"text","marks":[{"type":"strong"}]},{"text":": candidate score must improve or hold even vs ","type":"text"},{"text":"best_score","type":"text","marks":[{"type":"code_inline"}]},{"text":", respecting ","type":"text"},{"text":"benchmark_direction","type":"text","marks":[{"type":"code_inline"}]},{"text":" (","type":"text"},{"text":"higher_is_better","type":"text","marks":[{"type":"code_inline"}]},{"text":": score >= best_score; ","type":"text"},{"text":"lower_is_better","type":"text","marks":[{"type":"code_inline"}]},{"text":": score \u003c= best_score)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Merge","type":"text","marks":[{"type":"strong"}]},{"text":" via ","type":"text"},{"text":"oh-my-claudecode:git-master","type":"text","marks":[{"type":"code_inline"}]},{"text":": ","type":"text"},{"text":"git merge experiment/round_{n}_executor_{id} --no-ff -m \"Iteration {n}: {hypothesis} (score: {before} → {after})\"","type":"text","marks":[{"type":"code_inline"}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Re-benchmark","type":"text","marks":[{"type":"strong"}]},{"text":" on merged state to confirm improvement","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"If re-benchmark ","type":"text"},{"text":"confirms","type":"text","marks":[{"type":"strong"}]},{"text":" improvement: ","type":"text"},{"text":"accept winner","type":"text","marks":[{"type":"strong"}]},{"text":", break loop","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"If re-benchmark shows ","type":"text"},{"text":"regression","type":"text","marks":[{"type":"strong"}]},{"text":": ","type":"text"},{"text":"revert merge","type":"text","marks":[{"type":"strong"}]},{"text":" via ","type":"text"},{"text":"git -C {repo_path} reset --hard HEAD~1","type":"text","marks":[{"type":"code_inline"}]},{"text":", continue to next candidate","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"If merge ","type":"text"},{"text":"conflicts","type":"text","marks":[{"type":"strong"}]},{"text":": ","type":"text"},{"text":"git -C {repo_path} merge --abort","type":"text","marks":[{"type":"code_inline"}]},{"text":", continue to next candidate","type":"text"}]}]}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"If a winner was accepted AND ","type":"text"},{"text":"auto_push","type":"text","marks":[{"type":"code_inline"}]},{"text":" is ","type":"text"},{"text":"true","type":"text","marks":[{"type":"code_inline"}]},{"text":" in settings: ","type":"text"},{"text":"Push","type":"text","marks":[{"type":"strong"}]},{"text":" improvement branch: ","type":"text"},{"text":"git -C {repo_path} push origin improve/{goal_slug}","type":"text","marks":[{"type":"code_inline"}]},{"text":" (non-blocking). 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