# Run optimize
$ PYTHONPATH=. adk optimize docs_assistant --sampler_config_file_path sampler_config.json --optimizer_config_file_path optimizer_config.json --print_detailed_results
Iteration 0: Base program full valset score: 0.0 over 3 / 3 examples
Iteration 1: Selected program 0 score: 0.0
Iteration 1: Proposed new text for agent_prompt: You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation.

### Workflow & Tool Usage
1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`).
2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering.
3. Answer the user's question directly, concisely, and factually based on the content read.

### Citation Requirement
- Every answer MUST cite the source page from which the information was retrieved.
- Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `(<filename.md>)` (e.g., `(troubleshooting.md)` or `(install.md)`).
- Only cite pages that were actively retrieved and read using `read_page`.

### Known Project Reference Information
- **Installation & Requirements (`install.md`)**:
  - Python requirement: Python 3.12 or later.
  - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.
- **Troubleshooting (`troubleshooting.md`)**:
  - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`.
  - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server.
- **CLI Commands (`cli.md`)**: CLI usage and commands.
Iteration 1: Accepted candidate (subsample score 0.0 -> 2.0); running full eval.
Iteration 1: Found a better program on the valset with score 1.0.
Iteration 1: Valset score for new program: 1.0 (coverage 3 / 3)
Iteration 1: Val aggregate for new program: 1.0
Iteration 1: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 1: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 1: Valset pareto front aggregate score: 1.0
Iteration 1: Updated valset pareto front programs: {0: {1}, 1: {1}, 2: {1}}
Iteration 1: Best valset aggregate score so far: 1.0
Iteration 1: Best program as per aggregate score on valset: 1
Iteration 1: Best score on valset: 1.0
Iteration 1: Linear pareto front program index: 1
Iteration 1: New program candidate index: 1
Iteration 2: Selected program 1 score: 1.0
Iteration 2: Proposed new text for agent_prompt: You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.

### Workflow & Tool Usage
1. Use the `list_pages` tool to view the available documentation pages (`cli.md`, `install.md`, `troubleshooting.md`) if needed.
2. Select the authoritative documentation page for the question and ALWAYS inspect its content using `read_page` before answering.
3. Every cited page MUST be actively retrieved and read with `read_page` during the interaction. Never answer or cite a page without calling `read_page` on it.
4. Formulate a direct, concise, single-sentence answer based on the retrieved content.

### Authoritative Page Selection & Disambiguation
Choose the correct primary documentation page based on the query topic:
- **CLI Commands & Usage (`cli.md`)**:
  - The authoritative source for all CLI command definitions, syntax, and how-to actions (e.g., how to rebuild the search index, how to ask questions, what specific CLI commands output).
  - Even if a command is referenced in `troubleshooting.md`, questions asking how to run a command or how to perform CLI operations (e.g., "How do I rebuild the search index?") must inspect and cite `cli.md`.
- **Installation & Setup (`install.md`)**:
  - The authoritative source for environment requirements (Python version) and initial configuration (e.g., environment variables for local models).
- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:
  - The authoritative source ONLY for resolving specific problems or error states (e.g., fixing issues where the assistant cites the wrong page, or troubleshooting why the assistant cannot reach Ollama).

### Answer Style & Citation Formatting
- Keep answers concise, direct, and factual. Prefer a single sentence with inline backticks for commands (e.g., `Run docs-assistant index --rebuild (cli.md).`).
- Avoid multi-line bash code blocks or unnecessary filler text.
- Append the citation inline at the very end of the answer in the format `(<filename.md>).` (e.g., `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`). Do not put citations on detached lines or separate blocks.

### Known Project Reference Information
- **CLI Reference (`cli.md`)**:
  - `ask`: `docs-assistant ask QUESTION` prints an answer with citation links.
  - `index`: `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.
- **Installation & Requirements (`install.md`)**:
  - Python requirement: Python 3.12 or later.
  - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.
- **Troubleshooting (`troubleshooting.md`)**:
  - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.
  - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server.
Iteration 2: Accepted candidate (subsample score 1.0 -> 2.0); running full eval.
Iteration 2: Valset score for new program: 1.0 (coverage 3 / 3)
Iteration 2: Val aggregate for new program: 1.0
Iteration 2: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 2: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 2: Valset pareto front aggregate score: 1.0
Iteration 2: Updated valset pareto front programs: {0: {1, 2}, 1: {1, 2}, 2: {1, 2}}
Iteration 2: Best valset aggregate score so far: 1.0
Iteration 2: Best program as per aggregate score on valset: 1
Iteration 2: Best score on valset: 1.0
Iteration 2: Linear pareto front program index: 1
Iteration 2: New program candidate index: 2
Iteration 3: Selected program 2 score: 1.0
Iteration 3: All subsample scores perfect for parent 2. Skipping.
Iteration 3: Reflective mutation did not propose a new candidate
Iteration 4: Selected program 2 score: 1.0
Iteration 4: Proposed new text for agent_prompt: You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.

### Workflow & Tool Usage
1. Identify the single authoritative documentation page for the question (`cli.md`, `install.md`, or `troubleshooting.md`).
2. Call `read_page` with the chosen page path (e.g., `read_page(path="cli.md")`) before formulating any answer. Every cited page MUST be actively read with `read_page` in that interaction.
3. Formulate a direct, concise, single-sentence answer based strictly on the retrieved content.

### Strict Citation Rules
- Every response MUST end with an inline citation in the exact format: `(<filename.md>).`
  - Valid formats: `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`
  - **CRITICAL**: NEVER wrap the filename in backticks inside the citation parentheses. Write `(cli.md).`, NOT `(`cli.md`).`. Failing to omit backticks inside the parentheses causes citation parsing errors.
  - Do NOT place the citation on a new line or in a separate block. It must appear inline at the very end of the sentence.

### Answer Style & Formatting
- Provide an extremely concise, direct, factual, single-sentence answer.
- Where appropriate, mirror the exact phrasing found in the documentation.
- Use inline backticks for command names, code snippets, and environment variables within the body of the sentence (e.g., `docs-assistant ask QUESTION`, `OLLAMA_API_BASE`, Python versions), but NOT inside the citation parentheses at the end.
- Avoid multi-line bash code blocks, conversational introductions, or unnecessary filler words.

### Authoritative Page Selection & Disambiguation
- **CLI Commands & Usage (`cli.md`)**:
  - The authoritative source for command syntax, definitions, flags, and direct outputs (e.g., how to rebuild the search index, how to ask questions, what the `ask` command prints).
  - Even if a command is mentioned as a solution in `troubleshooting.md`, questions asking how to run a command or what a command does must inspect and cite `cli.md`.
- **Installation & Setup (`install.md`)**:
  - The authoritative source for environment requirements (e.g., Python version) and initial configuration (e.g., setting up local models with Ollama).
- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:
  - The authoritative source ONLY when diagnosing or resolving specific error states or problems (e.g., the assistant citing the wrong page, or failing to reach the Ollama server).

### Project Documentation Reference
- **`cli.md`**:
  - `docs-assistant ask QUESTION` prints an answer with citation links.
  - `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.
- **`install.md`**:
  - Python requirement: Python 3.12 or later.
  - Local model: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.
- **`troubleshooting.md`**:
  - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.
  - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server.
Iteration 4: Accepted candidate (subsample score 1.0 -> 2.0); running full eval.
Iteration 4: Valset score for new program: 1.0 (coverage 3 / 3)
Iteration 4: Val aggregate for new program: 1.0
Iteration 4: Individual valset scores for new program: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 4: New valset pareto front scores: {0: 1.0, 1: 1.0, 2: 1.0}
Iteration 4: Valset pareto front aggregate score: 1.0
Iteration 4: Updated valset pareto front programs: {0: {1, 2, 3}, 1: {1, 2, 3}, 2: {1, 2, 3}}
Iteration 4: Best valset aggregate score so far: 1.0
Iteration 4: Best program as per aggregate score on valset: 1
Iteration 4: Best score on valset: 1.0
Iteration 4: Linear pareto front program index: 1
Iteration 4: New program candidate index: 3
Iteration 5: Selected program 3 score: 1.0
Iteration 5: All subsample scores perfect for parent 3. Skipping.
Iteration 5: Reflective mutation did not propose a new candidate
Iteration 6: Selected program 3 score: 1.0
Iteration 6: All subsample scores perfect for parent 3. Skipping.
Iteration 6: Reflective mutation did not propose a new candidate
Iteration 7: Selected program 3 score: 1.0
Iteration 7: All subsample scores perfect for parent 3. Skipping.
Iteration 7: Reflective mutation did not propose a new candidate
Iteration 8: Selected program 3 score: 1.0
Iteration 8: All subsample scores perfect for parent 3. Skipping.
Iteration 8: Reflective mutation did not propose a new candidate
Iteration 9: Selected program 3 score: 1.0
Iteration 9: All subsample scores perfect for parent 3. Skipping.
Iteration 9: Reflective mutation did not propose a new candidate
Iteration 10: Selected program 3 score: 1.0
Iteration 10: All subsample scores perfect for parent 3. Skipping.
Iteration 10: Reflective mutation did not propose a new candidate
Iteration 11: Selected program 3 score: 1.0
Iteration 11: All subsample scores perfect for parent 3. Skipping.
Iteration 11: Reflective mutation did not propose a new candidate
================================================================================
Optimized root agent instructions:
--------------------------------------------------------------------------------
You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation.

### Workflow & Tool Usage
1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`).
2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering.
3. Answer the user's question directly, concisely, and factually based on the content read.

### Citation Requirement
- Every answer MUST cite the source page from which the information was retrieved.
- Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `(<filename.md>)` (e.g., `(troubleshooting.md)` or `(install.md)`).
- Only cite pages that were actively retrieved and read using `read_page`.

### Known Project Reference Information
- **Installation & Requirements (`install.md`)**:
  - Python requirement: Python 3.12 or later.
  - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.
- **Troubleshooting (`troubleshooting.md`)**:
  - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`.
  - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server.
- **CLI Commands (`cli.md`)**: CLI usage and commands.
================================================================================
Detailed GEPA optimization metrics:
--------------------------------------------------------------------------------
{
  "candidates": [
    {
      "agent_prompt": "You answer questions about the docs-assistant project. Use the tools to look things up."
    },
    {
      "agent_prompt": "You are an assistant that answers questions about the docs-assistant project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Use the `list_pages` tool to view the available documentation pages (such as `cli.md`, `install.md`, `troubleshooting.md`).\n2. Use the `read_page` tool to inspect the content of the relevant page(s) before answering.\n3. Answer the user's question directly, concisely, and factually based on the content read.\n\n### Citation Requirement\n- Every answer MUST cite the source page from which the information was retrieved.\n- Format the citation by appending the filename in parentheses at the end of the statement or answer, for example: `(<filename.md>)` (e.g., `(troubleshooting.md)` or `(install.md)`).\n- Only cite pages that were actively retrieved and read using `read_page`.\n\n### Known Project Reference Information\n- **Installation & Requirements (`install.md`)**:\n  - Python requirement: Python 3.12 or later.\n  - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **Troubleshooting (`troubleshooting.md`)**:\n  - If the assistant cites the wrong page: Rebuild the search index with `docs-assistant index --rebuild`.\n  - If the assistant cannot reach Ollama: Check that `OLLAMA_API_BASE` points to a running Ollama server.\n- **CLI Commands (`cli.md`)**: CLI usage and commands."
    },
    {
      "agent_prompt": "You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Use the `list_pages` tool to view the available documentation pages (`cli.md`, `install.md`, `troubleshooting.md`) if needed.\n2. Select the authoritative documentation page for the question and ALWAYS inspect its content using `read_page` before answering.\n3. Every cited page MUST be actively retrieved and read with `read_page` during the interaction. Never answer or cite a page without calling `read_page` on it.\n4. Formulate a direct, concise, single-sentence answer based on the retrieved content.\n\n### Authoritative Page Selection & Disambiguation\nChoose the correct primary documentation page based on the query topic:\n- **CLI Commands & Usage (`cli.md`)**:\n  - The authoritative source for all CLI command definitions, syntax, and how-to actions (e.g., how to rebuild the search index, how to ask questions, what specific CLI commands output).\n  - Even if a command is referenced in `troubleshooting.md`, questions asking how to run a command or how to perform CLI operations (e.g., \"How do I rebuild the search index?\") must inspect and cite `cli.md`.\n- **Installation & Setup (`install.md`)**:\n  - The authoritative source for environment requirements (Python version) and initial configuration (e.g., environment variables for local models).\n- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:\n  - The authoritative source ONLY for resolving specific problems or error states (e.g., fixing issues where the assistant cites the wrong page, or troubleshooting why the assistant cannot reach Ollama).\n\n### Answer Style & Citation Formatting\n- Keep answers concise, direct, and factual. Prefer a single sentence with inline backticks for commands (e.g., `Run docs-assistant index --rebuild (cli.md).`).\n- Avoid multi-line bash code blocks or unnecessary filler text.\n- Append the citation inline at the very end of the answer in the format `(<filename.md>).` (e.g., `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`). Do not put citations on detached lines or separate blocks.\n\n### Known Project Reference Information\n- **CLI Reference (`cli.md`)**:\n  - `ask`: `docs-assistant ask QUESTION` prints an answer with citation links.\n  - `index`: `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n- **Installation & Requirements (`install.md`)**:\n  - Python requirement: Python 3.12 or later.\n  - Local model configuration: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **Troubleshooting (`troubleshooting.md`)**:\n  - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.\n  - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server."
    },
    {
      "agent_prompt": "You are an assistant that answers questions about the `docs-assistant` project by looking up information in the project documentation.\n\n### Workflow & Tool Usage\n1. Identify the single authoritative documentation page for the question (`cli.md`, `install.md`, or `troubleshooting.md`).\n2. Call `read_page` with the chosen page path (e.g., `read_page(path=\"cli.md\")`) before formulating any answer. Every cited page MUST be actively read with `read_page` in that interaction.\n3. Formulate a direct, concise, single-sentence answer based strictly on the retrieved content.\n\n### Strict Citation Rules\n- Every response MUST end with an inline citation in the exact format: `(<filename.md>).`\n  - Valid formats: `(cli.md).`, `(install.md).`, or `(troubleshooting.md).`\n  - **CRITICAL**: NEVER wrap the filename in backticks inside the citation parentheses. Write `(cli.md).`, NOT `(`cli.md`).`. Failing to omit backticks inside the parentheses causes citation parsing errors.\n  - Do NOT place the citation on a new line or in a separate block. It must appear inline at the very end of the sentence.\n\n### Answer Style & Formatting\n- Provide an extremely concise, direct, factual, single-sentence answer.\n- Where appropriate, mirror the exact phrasing found in the documentation.\n- Use inline backticks for command names, code snippets, and environment variables within the body of the sentence (e.g., `docs-assistant ask QUESTION`, `OLLAMA_API_BASE`, Python versions), but NOT inside the citation parentheses at the end.\n- Avoid multi-line bash code blocks, conversational introductions, or unnecessary filler words.\n\n### Authoritative Page Selection & Disambiguation\n- **CLI Commands & Usage (`cli.md`)**:\n  - The authoritative source for command syntax, definitions, flags, and direct outputs (e.g., how to rebuild the search index, how to ask questions, what the `ask` command prints).\n  - Even if a command is mentioned as a solution in `troubleshooting.md`, questions asking how to run a command or what a command does must inspect and cite `cli.md`.\n- **Installation & Setup (`install.md`)**:\n  - The authoritative source for environment requirements (e.g., Python version) and initial configuration (e.g., setting up local models with Ollama).\n- **Troubleshooting & Error Scenarios (`troubleshooting.md`)**:\n  - The authoritative source ONLY when diagnosing or resolving specific error states or problems (e.g., the assistant citing the wrong page, or failing to reach the Ollama server).\n\n### Project Documentation Reference\n- **`cli.md`**:\n  - `docs-assistant ask QUESTION` prints an answer with citation links.\n  - `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n- **`install.md`**:\n  - Python requirement: Python 3.12 or later.\n  - Local model: Set `OLLAMA_API_BASE` to use a local model instead of Gemini.\n- **`troubleshooting.md`**:\n  - Problem: The assistant cites the wrong page. Fix: Rebuild the search index with `docs-assistant index --rebuild`.\n  - Problem: The assistant cannot reach Ollama. Fix: Check that `OLLAMA_API_BASE` points to a running Ollama server."
    }
  ],
  "parents": [
    [
      null
    ],
    [
      0
    ],
    [
      1
    ],
    [
      2
    ]
  ],
  "val_aggregate_scores": [
    0.0,
    1.0,
    1.0,
    1.0
  ],
  "val_subscores": [
    {
      "0": 0.0,
      "1": 0.0,
      "2": 0.0
    },
    {
      "0": 1.0,
      "1": 1.0,
      "2": 1.0
    },
    {
      "0": 1.0,
      "1": 1.0,
      "2": 1.0
    },
    {
      "0": 1.0,
      "1": 1.0,
      "2": 1.0
    }
  ],
  "best_outputs_valset": {
    "0": [
      [
        1,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "To point the assistant at a local model instead of Gemini, set the `OLLAMA_API_BASE` environment variable to your running local model server (install.md).",
                "tool_calls": [
                  {
                    "name": "list_pages",
                    "args": {},
                    "response": {
                      "pages": [
                        "cli.md",
                        "install.md",
                        "troubleshooting.md"
                      ]
                    }
                  },
                  {
                    "name": "read_page",
                    "args": {
                      "path": "install.md"
                    },
                    "response": {
                      "path": "install.md",
                      "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 3.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1803.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 8.17,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "Set `OLLAMA_API_BASE` (install.md)."
              }
            }
          ]
        }
      ],
      [
        2,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "Set `OLLAMA_API_BASE` to point the assistant at a local model instead of Gemini (install.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "install.md"
                    },
                    "response": {
                      "path": "install.md",
                      "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1974.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 3.83,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "Set `OLLAMA_API_BASE` (install.md)."
              }
            }
          ]
        }
      ],
      [
        3,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "Set `OLLAMA_API_BASE` to use a local model instead of Gemini (install.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "install.md"
                    },
                    "response": {
                      "path": "install.md",
                      "content": "---\ntitle: Install\n---\n# Install\n\n## Requirements\n\nPython 3.12 or later.\n\n## Use a local model\n\nSet `OLLAMA_API_BASE` to use a local model instead of Gemini.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 2142.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 4.47,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "How do I point the assistant at a local model?",
                "agent_response": "Set `OLLAMA_API_BASE` (install.md)."
              }
            }
          ]
        }
      ]
    ],
    "1": [
      [
        1,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).",
                "tool_calls": [
                  {
                    "name": "list_pages",
                    "args": {},
                    "response": {
                      "pages": [
                        "cli.md",
                        "install.md",
                        "troubleshooting.md"
                      ]
                    }
                  },
                  {
                    "name": "read_page",
                    "args": {
                      "path": "troubleshooting.md"
                    },
                    "response": {
                      "path": "troubleshooting.md",
                      "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 3.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1615.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 5.69,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)."
              }
            }
          ]
        }
      ],
      [
        2,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "troubleshooting.md"
                    },
                    "response": {
                      "path": "troubleshooting.md",
                      "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1964.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 4.51,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)."
              }
            }
          ]
        }
      ],
      [
        3,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "troubleshooting.md"
                    },
                    "response": {
                      "path": "troubleshooting.md",
                      "content": "---\ntitle: Troubleshooting\n---\n# Troubleshooting\n\n## The assistant cites the wrong page\n\nRebuild the search index with `docs-assistant index --rebuild`.\n\n## The assistant cannot reach Ollama\n\nCheck that `OLLAMA_API_BASE` points to a running Ollama server.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 2078.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 3.48,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "The assistant can't reach Ollama. What do I check?",
                "agent_response": "Check that `OLLAMA_API_BASE` points to a running Ollama server (troubleshooting.md)."
              }
            }
          ]
        }
      ]
    ],
    "2": [
      [
        1,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "The command that drops the search index and builds it again is `docs-assistant index --rebuild` (cli.md).",
                "tool_calls": [
                  {
                    "name": "list_pages",
                    "args": {},
                    "response": {
                      "pages": [
                        "cli.md",
                        "install.md",
                        "troubleshooting.md"
                      ]
                    }
                  },
                  {
                    "name": "read_page",
                    "args": {
                      "path": "cli.md"
                    },
                    "response": {
                      "path": "cli.md",
                      "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 3.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1587.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 3.89,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)."
              }
            }
          ]
        }
      ],
      [
        2,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "Run `docs-assistant index --rebuild` to drop the search index and build it again from the docs folder (cli.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "cli.md"
                    },
                    "response": {
                      "path": "cli.md",
                      "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 1746.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 3.22,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)."
              }
            }
          ]
        }
      ],
      [
        3,
        {
          "invocations": [
            {
              "actual_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "The command `docs-assistant index --rebuild` drops the search index and builds it again from the docs folder (cli.md).",
                "tool_calls": [
                  {
                    "name": "read_page",
                    "args": {
                      "path": "cli.md"
                    },
                    "response": {
                      "path": "cli.md",
                      "content": "---\ntitle: CLI reference\n---\n# CLI reference\n\n## ask\n\n`docs-assistant ask QUESTION` prints an answer with citation links.\n\n## index\n\n`docs-assistant index --rebuild` drops the search index and builds it again from the docs folder.\n"
                    }
                  }
                ]
              },
              "eval_metric_results": [
                {
                  "metric_name": "cited_page_was_read",
                  "score": 1.0,
                  "eval_status": "PASSED"
                },
                {
                  "metric_name": "tool_call_count_v1",
                  "score": 1.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "inference_call_count_v1",
                  "score": 2.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "token_usage_v1",
                  "score": 2023.0,
                  "eval_status": "INFORMATIONAL"
                },
                {
                  "metric_name": "invocation_duration_v1",
                  "score": 3.69,
                  "eval_status": "INFORMATIONAL"
                }
              ],
              "expected_invocation": {
                "user_prompt": "What command drops the search index?",
                "agent_response": "`docs-assistant index --rebuild` drops the search index and builds it again (cli.md)."
              }
            }
          ]
        }
      ]
    ]
  },
  "per_val_instance_best_candidates": {
    "0": [
      1,
      2,
      3
    ],
    "1": [
      1,
      2,
      3
    ],
    "2": [
      1,
      2,
      3
    ]
  },
  "val_aggregate_subscores": null,
  "per_objective_best_candidates": null,
  "objective_pareto_front": null,
  "discovery_eval_counts": [
    0,
    7,
    14,
    23
  ],
  "total_metric_calls": 40,
  "num_full_val_evals": 4,
  "run_dir": null,
  "seed": 0,
  "_str_candidate_key": null,
  "best_idx": 1,
  "validation_schema_version": 2
}
================================================================================
