data/processed/RQ1/SocialMediaManager-MCP/reference_trajectory.yaml

# Full reference trajectory configuration - SocialMediaManager-MCP
#
# Version: ideal trajectory derived from the code design (applicable to all models)
# Principle: include only steps explicitly required by the code design, not based on test statistics
#
# Code-design analysis:
# 1. Execution flow (orchestrator.py):
#    - The Orchestrator manages the whole workflow with two layers of retry logic:
#      (a) Orchestrator-level retry: for unexpected exceptions (up to 3 attempts; MAX_CREW_RETRIES=2)
#      (b) Business-logic retry: for validation failures (up to 6 attempts; max_retries=5)
#    - Ideal flow (no retries):
#      Step 1: Topic Analysis (TopicAnalyzerCrew)
#      Step 2-4: Content Generation with Feedback Loop
#        - Generate X post (ShakespeareGeneratorCrew)
#        - Validate X post (PostReviewCrew)
#        - If valid=True, stop the loop; otherwise retry
#      Step 5: Save Results
#
# 2. Agent structure of the three crews:
#    - TopicAnalyzerCrew (topic_analyzer/topic_analyzer_crew.py):
#      - Agent: Topic Analysis Expert
#        Tools: keyword_extractor, topic_complexity_analyzer
#    - ShakespeareGeneratorCrew (content_generator/shakespeare_generator_crew.py):
#      - Agent: Shakespearean Bard
#        Tools: keyword_extractor, character_counter_tool, emoji_detector_tool,
#              post_structure_validator, shakespearean_style_detector, tone_analyzer
#    - PostReviewCrew (post_reviewer/post_review_crew.py):
#      - Agent: X Post Verifier
#        Tools: character_counter_tool, emoji_detector_tool, post_structure_validator,
#              shakespearean_style_detector, tone_analyzer
#
# 3. SPAN hierarchy:
#    - shakespeare_x_post_orchestrator (top-level; orchestrator.py line 347)
#      └─ crew_execution (contains retry logic; orchestrator.py line 362-393)
#         ├─ topic_analysis (topic analysis; orchestrator.py line 114-141)
#         └─ content_generation_loop (content generation + review loop; orchestrator.py line 143-250)
#            Includes multiple iterations:
#            - ShakespeareGeneratorCrew.kickoff (generate X post)
#            - PostReviewCrew.kickoff (validate X post)
#            - If valid=True then stop; otherwise continue
#
# 4. MCP tools (tools/mcp_server.py):
#    - Character count: character_counter_tool (validate 200-280 characters)
#    - Emoji detection: emoji_detector_tool (ensure no emoji)
#    - Structure validation: post_structure_validator (validate 1-3-1 structure, 5 lines)
#    - Style detection: shakespearean_style_detector (detect Shakespearean style elements)
#    - Tone analysis: tone_analyzer (ensure satire and humor)
#    - Keyword extraction: keyword_extractor (extract key topic concepts)
#    - Complexity analysis: topic_complexity_analyzer (estimate topic complexity)

# Project name
project_name: "SocialMediaManager-MCP"

# Trajectory extraction types
extract_types:
  - "SPAN" # Multi-level SPAN hierarchy
  - "Chain" # Each Crew kickoff chain
  - "Agent" # Agents inside each Crew
  - "LLM" # LLM calls
  - "Tool" # MCP tool calls

# Repeatable pattern configuration
# SocialMediaManager-MCP has a self-evaluation loop (ideal trajectory uses only 1 iteration)
repeatable_patterns: []

# ============================================================================
# Reference trajectory (ground truth) - derived from the code design
# ============================================================================
#
# Diagram (ideal execution path: no retries, no errors, first generation passes validation):
#
# [SPAN] shakespeare_x_post_orchestrator
# └─ [SPAN] crew_execution
#    ├─ [SPAN] topic_analysis
#    │  └─ [Chain] Crew***.kickoff
#    │     └─ [AGENT] Topic Analysis Expert
#    │        ├─ [LLM] * (understand the topic)
#    │        ├─ [Tool] keyword_extractor (extract keywords)
#    │        ├─ [LLM] * (analyze extracted keywords)
#    │        ├─ [Tool] topic_complexity_analyzer (analyze complexity)
#    │        └─ [LLM] * (produce topic analysis report)
#    └─ [SPAN] content_generation_loop
#       ├─ [Chain] Crew***.kickoff (ShakespeareGeneratorCrew - iteration 1 generation)
#       │  └─ [AGENT] Shakespearean Bard
#       │     ├─ [LLM] * (plan the generation strategy)
#       │     ├─ [Tool] keyword_extractor (understand topic keywords)
#       │     ├─ [LLM] * (draft the initial X post)
#       │     ├─ [Tool] character_counter_tool (check character count)
#       │     ├─ [LLM] * (adjust character count)
#       │     ├─ [Tool] emoji_detector_tool (check emoji)
#       │     ├─ [LLM] * (confirm no emoji)
#       │     ├─ [Tool] post_structure_validator (validate 1-3-1 structure)
#       │     ├─ [LLM] * (adjust structure)
#       │     ├─ [Tool] shakespearean_style_detector (check style)
#       │     ├─ [LLM] * (strengthen style)
#       │     ├─ [Tool] tone_analyzer (check tone)
#       │     └─ [LLM] * (final polish and output)
#       └─ [Chain] Crew***.kickoff (PostReviewCrew - iteration 1 validation)
#          └─ [AGENT] X Post Verifier
#             ├─ [LLM] * (read and do an initial assessment)
#             ├─ [Tool] character_counter_tool (validate character count)
#             ├─ [LLM] * (record character count result)
#             ├─ [Tool] emoji_detector_tool (validate no emoji)
#             ├─ [LLM] * (record emoji check result)
#             ├─ [Tool] post_structure_validator (validate 1-3-1 structure)
#             ├─ [LLM] * (record structure check result)
#             ├─ [Tool] shakespearean_style_detector (validate style)
#             ├─ [LLM] * (record style check result)
#             ├─ [Tool] tone_analyzer (validate tone)
#             └─ [LLM] * (final decision, output valid=True)
#
# Design basis:
# - orchestrator.py: execute topic_analysis → content_generation_loop sequentially
# - TopicAnalyzerCrew contains 1 Agent, using 2 tools to analyze the topic
# - ShakespeareGeneratorCrew contains 1 Agent, using multiple tools for generation and self-validation
# - PostReviewCrew contains 1 Agent, using multiple tools for comprehensive validation
# - Ideal situation: first generation passes validation (valid=True), no retries needed
# - All Agent roles are defined in each crew's config/agents.yaml
# - All tasks are defined in each crew's config/tasks.yaml, specifying the use of specific tools
# - Tools are obtained from the MCP server through MCPServerAdapter
# - PostReviewCrew contains 1 Agent, using multiple tools for comprehensive validation
# - Ideal situation: first generation passes validation (valid=True), no retries needed
# - All Agent roles are defined in each crew's config/agents.yaml
# - All tasks are defined in each crew's config/tasks.yaml, specifying the use of specific tools
# - Tools are obtained from the MCP server through MCPServerAdapter
#
# Ideal trajectory notes:
# - Top-level SPAN: shakespeare_x_post_orchestrator
# - Second-level SPAN: crew_execution (contains two layers of retry logic)
# - Two sub-SPANs executed sequentially: topic_analysis → content_generation_loop
# - Topic analysis stage: Topic Analyst uses keyword_extractor and topic_complexity_analyzer
# - content_generation_loop stage contains a self-evaluation loop:
#   - Iteration 1 (ideal case):
#     * ShakespeareGeneratorCrew generates the X post and self-validates with multiple tools
#     * PostReviewCrew validates the X post using all required validation tools and returns valid=True
#   - No iterations 2-N needed (because iteration 1 already passes)
# - This trajectory represents the ideal execution path: no retries and no errors
#
# Notes:
# - "LLM: *" means any LLM model (wildcard match)
# - Agent names must exactly match the role field in agents.yaml
# - Tool names must exactly match tool names provided by the MCP server
# - Both Generator and Verifier use multiple tools (as required by tasks.yaml)
# - Tool call order may vary by agent decisions
# - Some LLM calls may be merged/split, but core tool calls must appear
# ============================================================================

reference_trajectory:
  # ===== Top-level SPAN =====
  - "SPAN: shakespeare_x_post_orchestrator"

  # ===== Second-level SPAN (contains two layers of retry logic) =====
  - "SPAN: crew_execution"

  # ===== Stage 1: Topic Analysis (TopicAnalyzerCrew) =====
  - "SPAN: topic_analysis"
  - "Chain: Crew***.kickoff"
  - "Agent: Topic Analysis Expert"
  - "LLM: *" # Initial understanding of the topic and analysis planning
  - "Tool: keyword_extractor" # Required by tasks.yaml (no order constraint)
  - "LLM: *" # Analyze keyword extraction results
  - "Tool: topic_complexity_analyzer" # Required by tasks.yaml (no order constraint)
  - "LLM: *" # Synthesize and produce the topic insight report

  # ===== Stage 2: Content Generation Loop (Self-Evaluation Loop) =====
  - "SPAN: content_generation_loop"

  # === Iteration 1: Content generation (ShakespeareGeneratorCrew) ===
  - "Chain: Crew***.kickoff"
  - "Agent: Shakespearean Bard"
  - "LLM: *" # Understand topic and topic_insights; plan generation strategy
  - "Tool: keyword_extractor" # MUST be first: tasks.yaml STEP 1 requires it
  - "LLM: *" # Draft the initial X post based on extracted keywords
  # The following tools are required by tasks.yaml for validation (no order constraint):
  - "Tool: character_counter_tool" # Validate character count (200-280)
  - "LLM: *" # Adjust based on character count results
  - "Tool: emoji_detector_tool" # Ensure no emoji
  - "LLM: *" # Confirm emoji check passes
  - "Tool: post_structure_validator" # Validate 1-3-1 structure (5 lines)
  - "LLM: *" # Adjust based on structure results
  - "Tool: shakespearean_style_detector" # Check Shakespearean style
  - "LLM: *" # Strengthen style elements
  - "Tool: tone_analyzer" # Validate satire/humor tone
  - "LLM: *" # Final polish and output the X post

  # === Iteration 1: Content verification (PostReviewCrew) ===
  - "Chain: Crew***.kickoff"
  - "Agent: X Post Verifier"
  - "LLM: *" # Read the X post and plan a verification strategy
  # The following 5 tools are REQUIRED by tasks.yaml (no order constraint):
  - "Tool: character_counter_tool" # Validate character count (200-280)
  - "LLM: *" # Analyze character count results
  - "Tool: emoji_detector_tool" # Validate no emoji
  - "LLM: *" # Analyze emoji check results
  - "Tool: post_structure_validator" # Validate 1-3-1 structure (5 lines)
  - "LLM: *" # Analyze structure results
  - "Tool: shakespearean_style_detector" # Validate Shakespearean style
  - "LLM: *" # Analyze style results
  - "Tool: tone_analyzer" # Validate satire/humor tone
  - "LLM: *" # Combine all results; output valid=True, feedback=""

# Target tool list (for the single-tool-use metric)
# This lists all tools filtered for each agent in the configuration
target_tools:
  # Topic Analysis stage
  - "Tool: keyword_extractor"
  - "Tool: topic_complexity_analyzer"
  # Content Generation stage
  - "Tool: character_counter_tool"
  - "Tool: emoji_detector_tool"
  - "Tool: post_structure_validator"
  - "Tool: shakespearean_style_detector"
  - "Tool: tone_analyzer"
  # Post Review stage (shares tools with Generation; not duplicated)

# ============================================================================
# Dynamic tool permutation configuration
# ============================================================================
# Define permutable tool groups for some stages to generate reference trajectories
# with different tool orders. During evaluation, all permutations are tried and
# the best-matching one is selected as the reference.
#
# Notes:
# - Topic Analyst's two tools can be in any order (tasks.yaml does not specify)
# - Shakespearean Bard's keyword_extractor MUST be the first tool (explicitly required by tasks.yaml)
#   but the subsequent 5 validation tools can be in any order
# - X Post Verifier's 5 validation tools can be in any order (tasks.yaml does not specify)
permutable_tool_groups:
  # Topic Analysis stage tools can be in any order
  topic_analysis_tools:
    - "Tool: keyword_extractor"
    - "Tool: topic_complexity_analyzer"

  # Shakespearean Bard validation tools can be in any order
  # Note: the first keyword_extractor is NOT included (it must remain the first tool)
  shakespearean_bard_validation_tools:
    - "Tool: character_counter_tool"
    - "Tool: emoji_detector_tool"
    - "Tool: post_structure_validator"
    - "Tool: shakespearean_style_detector"
    - "Tool: tone_analyzer"

  # X Post Verifier validation tools can be in any order
  x_post_verifier_tools:
    - "Tool: character_counter_tool"
    - "Tool: emoji_detector_tool"
    - "Tool: post_structure_validator"
    - "Tool: shakespearean_style_detector"
    - "Tool: tone_analyzer"

# Models to evaluate
models:
  - "GPT-5"
  - "GPT-4o-mini"
  - "DeepSeek-V3-1"
  - "DeepSeek-R1"
  - "Gemini-2.5-flash"
  - "Gemini-2.5-flash-nothinking"
  - "Qwen3-235b"
# ============================================================================
# Usage
# ============================================================================
#
# 1. Trajectory hierarchy:
#    - Level 1: SPAN (shakespeare_x_post_orchestrator)
#    - Level 2: SPAN (crew_execution)
#    - Level 3: SPAN (topic_analysis, content_generation_loop)
#    - Level 4: Chain (Crew***.kickoff; wildcard-normalized UUID)
#    - Level 5: AGENT (exact match for agent role)
#    - Level 6: LLM (wildcard match for any model)
#    - Level 6: Tool (exact match for tool name)
#
# 2. Wildcard handling:
#    - Crew_<UUID>.kickoff -> Crew***.kickoff (handled by evaluate_trajectory.py)
#    - LLM: * -> matches any model name (e.g., gpt-4o-mini, deepseek-reasoner, gemini-2.5-flash)
#    - Agent names must match fully (including the complete role name)
#
# 3. Exact-match requirements:
#    - SPAN names: "shakespeare_x_post_orchestrator", "crew_execution",
#      "topic_analysis", "content_generation_loop"
#    - Chain name: "Crew***.kickoff" (wildcard match)
#    - Agent names: "Agent: Topic Analysis Expert",
#      "Agent: Shakespearean Bard",
#      "Agent: X Post Verifier"
#      (must exactly match the role field in agents.yaml)
#    - LLM name: "LLM: *" (wildcard match for any model)
#    - Tool names: must exactly match MCP tool names (keyword_extractor, topic_complexity_analyzer,
#      character_counter_tool, emoji_detector_tool, post_structure_validator,
#      shakespearean_style_detector, tone_analyzer)
#
# 4. Metric meanings:
#    - Exact Match: trajectories must be identical (including the number of LLM and tool calls)
#    - In-order Match: extra calls allowed, but core steps must appear in order
#    - Any-order Match: all required steps must appear (order ignored)
#    - Precision: fraction of predicted steps that are correct
#    - Recall: fraction of reference steps covered by the prediction
#    - Single-tool Use: checks usage of core tools
#    - unique_path_ratio: path diversity (unique full trajectories / samples)
#    - path_entropy: path entropy (Shannon entropy over trajectory frequencies, normalized to 0-1)
#
# 5. Run:
#    python3 evaluate_trajectory.py --config reference_trajectory.yaml
#
# 6. Design notes:
#    - This reference trajectory represents the ideal execution path (no retries, no errors)
#    - Two main stages execute sequentially: Topic Analysis → Content Generation Loop
#    - Stage 1 (Topic Analysis): Topic Analyst uses 2 tools to analyze the topic
#    - Stage 2 (Content Generation Loop): contains a self-evaluation loop
#      * Shakespearean Bard generates the X post and self-validates with multiple tools
#      * X Post Verifier performs comprehensive validation using all validation tools
#      * Ideal case: valid=True on the first attempt, no retries needed
#    - In-order Match and Recall are often more suitable for evaluating practical performance
#    - The reference trajectory defines only core required steps and allows extra tool/LLM calls
#
# 7. Differences from real trajectories:
#    - Real trajectories may include business-logic retries (validation failure triggers regeneration)
#    - Real trajectories may include orchestrator-level retries (exceptions trigger workflow retry)
#    - Generator may use a different tool order (but should still use tools required by tasks.yaml)
#    - Verifier may use a different tool order (but must use all 5 validation tools)
#    - Some reasoning models (e.g., DeepSeek-R1) may include many extra LLM calls
#    - Some models (e.g., Gemini) may skip tool calls and directly generate outputs (non-compliant)
#    - These differences are not necessarily errors, but skipping required tools or failing validation is abnormal
#
# 8. MCP version characteristics:
#    - All tools are provided by an MCP server using the SSE protocol
#    - Tools are obtained from the server via MCPServerAdapter
#    - Includes multi-level SPAN structure (orchestrator + crew_execution + 2 stage SPANs)
#    - Three specialized crews collaborate to generate Shakespeare-style X posts
#    - Each crew has a clear responsibility and an explicit set of available tools
#    - TopicAnalyzerCrew: 1 agent, analyzes the topic and extracts insights
#    - ShakespeareGeneratorCrew: 1 agent, generates and self-validates the X post
#    - PostReviewCrew: 1 agent, comprehensively validates the X post
#    - Tool categories: analysis tools (keyword_extractor, topic_complexity_analyzer) and
#      validation tools (character_counter_tool, emoji_detector_tool, post_structure_validator,
#      shakespearean_style_detector, tone_analyzer)
#
# 9. Business-logic notes:
#    - The self-evaluation loop is critical: generation must be followed by validation
#    - If validation fails (valid=False), regenerate with feedback (up to 6 attempts)
#    - If all attempts fail, the workflow ends and the failed X post is saved
#    - The ideal trajectory assumes the first generation passes validation (best case)
#    - Generator should self-validate using all tools required by tools.yaml
#    - Verifier must use all 5 validation tools for thorough validation
#    - Some real trajectories may include multiple generation-validation cycles (normal business retries)
#
# 10. Tool usage requirements (based on tasks.yaml):
#     - Topic Analyst (analyze_topic task):
#       * Explicit requirement: "Start by using the available analytical tools"
#       * Must use: keyword_extractor, topic_complexity_analyzer
#       * Order: none (tasks.yaml does not specify)
#     - Shakespearean Bard (write_x_post task):
#       * Explicit requirement: "STEP 1 - REQUIRED: First, use the keyword_extractor tool"
#       * Explicit requirement: "IMPORTANT: Before finalizing, use the available tools to verify quality"
#       * Must use: keyword_extractor (must be the first tool)
#       * Should use: character_counter_tool, emoji_detector_tool, post_structure_validator,
#                    shakespearean_style_detector, tone_analyzer (quality validation)
#       * Order: keyword_extractor must be first; remaining validation tools have no order constraint
#     - X Post Verifier (verify_x_post task):
#       * Explicit requirement: "CRITICAL: You MUST use the following tools to perform thorough validation"
#       * Must use: character_counter_tool, emoji_detector_tool, post_structure_validator,
#                  shakespearean_style_detector, tone_analyzer (all 5)
#       * Requirement: "Base your validation decision on these tool results, not assumptions"
#       * Order: none (tasks.yaml does not specify)
#
# 11. Tool ordering notes:
#     - **Ordered scenario**:
#       * Shakespearean Bard's keyword_extractor must be the first tool
#         (tasks.yaml line 7-8: "STEP 1 - REQUIRED: First, use the keyword_extractor tool")
#     - **Unordered scenarios**:
#       * Topic Analyst's two tools (keyword_extractor, topic_complexity_analyzer) can be in any order
#       * Shakespearean Bard's 5 validation tools can be in any order (as long as after keyword_extractor)
#       * X Post Verifier's 5 validation tools can be in any order
#     - **Order in the reference trajectory**:
#       * The listed order reflects common observed patterns
#       * Evaluation should allow flexible tool ordering (except the Bard's keyword_extractor-first constraint)
#       * The evaluator should enforce the "keyword_extractor must be first" constraint for the Bard
#
# 12. Dynamic tool permutation optimization:
#     - **Idea**: tool calls within each AGENT can have different orders
#     - **Mechanism**:
#       * permutable_tool_groups defines permutable tool groups
#       * The evaluator generates all tool-order permutations (Cartesian product)
#       * For each sample, select the permutation with the highest combined score across
#         exact_match, in_order_match, and any_order_match
#     - **Number of permutations**:
#       * topic_analysis_tools: 2! = 2
#       * shakespearean_bard_validation_tools: 5! = 120
#       * x_post_verifier_tools: 5! = 120
#       * Total: 2 × 120 × 120 = 28,800 candidate reference trajectories
#     - **Evaluation strategy**:
#       * Dynamically select the best reference trajectory per test sample
#       * Combined score = exact_match×3 + in_order_match×2 + any_order_match×1
#       * This is fairer and adapts to different models' tool-calling strategies
#     - **Notes**:
#       * The Bard's first keyword_extractor is not permuted (must remain first)
#       * Permutations are within an AGENT boundary only (not across AGENT boundaries)
#       * Tool permutations do not change the positions or counts of LLM calls