{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-automazeio--ccpm","slug":"automazeio--ccpm","name":"ccpm","type":"agent","url":"https://automaze.io","page_url":"https://unfragile.ai/automazeio--ccpm","categories":["ai-agents"],"tags":["ai-agents","ai-coding","claude","claude-code","project-management","vibe-coding"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-automazeio--ccpm__cap_0","uri":"capability://planning.reasoning.specification.driven.prd.to.code.transformation.pipeline","name":"specification-driven prd-to-code transformation pipeline","description":"Enforces a five-phase workflow (Brainstorm → PRD → Epic → Task → Code) where every line of code traces back to a specification document stored in .claude/prd/ directory. Uses GitHub Issues as the single source of truth and coordinates phase transitions through structured commands that validate completeness before advancing. Prevents context loss by maintaining explicit traceability between requirements and implementation artifacts.","intents":["I want to ensure every feature I build is tied to a written specification","I need to prevent scope creep and vibe-coding in my AI-assisted development","I want to maintain full traceability from product requirements to shipped code","I need a structured workflow that multiple AI agents can follow consistently"],"best_for":["teams building with AI agents who want specification discipline","solo developers using Claude Code who need structured workflows","projects requiring audit trails and requirement traceability"],"limitations":["Requires strict adherence to five-phase discipline — cannot skip phases without breaking workflow integrity","PRD documents must be manually written; system does not auto-generate requirements from user stories","Phase transitions are sequential; cannot parallelize PRD→Epic→Task decomposition steps","Workflow enforcement is convention-based through commands, not cryptographically enforced"],"requires":["GitHub repository with Issues enabled","Git with worktree support (Git 2.15+)","Claude API access (via Claude Code or direct API)",".claude/ directory structure initialized in project root"],"input_types":["markdown (PRD documents)","structured text (Epic/Task descriptions)","GitHub Issue metadata"],"output_types":["GitHub Issues (Epic and Task issues)","Git branches (one per worktree)","Code artifacts in isolated worktrees"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_1","uri":"capability://automation.workflow.parallel.ai.agent.execution.with.git.worktree.isolation","name":"parallel ai agent execution with git worktree isolation","description":"Deploys multiple specialized AI agents in parallel by creating isolated Git worktrees for each Task/Issue, preventing merge conflicts and context pollution. Each agent operates independently on its worktree while the main thread maintains strategic oversight. Uses Git worktree branching strategy to enable true parallelism without agents interfering with each other's work or context windows.","intents":["I want multiple AI agents to work on different tasks simultaneously without conflicts","I need to prevent context window pollution when agents work on the same codebase","I want to accelerate development by parallelizing work across multiple agents","I need agents to work in isolation but coordinate through a shared main branch"],"best_for":["teams running multiple Claude Code instances in parallel","large projects with 3+ concurrent work streams","development workflows where context isolation is critical"],"limitations":["Worktree creation adds ~500ms overhead per agent spawn","Merge conflicts still possible if agents modify overlapping files; requires manual resolution","No automatic conflict detection — relies on Git merge to surface issues","Worktree cleanup must be manual or scripted; no built-in garbage collection","Maximum practical parallelism limited by API rate limits and token budgets per agent"],"requires":["Git 2.15+ with worktree support","Sufficient disk space for N worktrees (each ~copy of codebase)","Multiple Claude API keys or rate-limit headroom for parallel requests","GitHub repository with write access for branch creation"],"input_types":["GitHub Issue (Task specification)","Git repository state","Agent configuration (specialized agent type)"],"output_types":["Git worktree (isolated branch)","Code changes in worktree","Pull request or merge back to main"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_10","uri":"capability://automation.workflow.command.driven.workflow.enforcement.with.phase.validation","name":"command-driven workflow enforcement with phase validation","description":"Implements workflow enforcement through structured commands (pm init, pm prd, pm epic, pm task, pm code) that validate phase completion before advancing. Each command checks preconditions (e.g., PRD must exist before creating Epics), updates GitHub Issues and .claude/ state, and provides feedback on workflow progress. Commands are the primary interface to the system, ensuring users follow the five-phase discipline rather than ad-hoc development.","intents":["I want the system to enforce workflow discipline and prevent skipping phases","I need clear feedback on what phase I'm in and what's required next","I want commands to validate preconditions before allowing phase transitions","I need a structured interface to the workflow, not free-form development"],"best_for":["teams wanting to enforce strict workflow discipline","projects where phase skipping is a common problem","developers who prefer command-driven interfaces over GUI tools"],"limitations":["Commands are shell-based; requires command-line familiarity","No GUI for non-technical stakeholders to interact with workflow","Commands are synchronous; long-running operations block the terminal","Error messages are text-based; no visual feedback on workflow state","No undo/rollback for commands; mistakes require manual correction"],"requires":["Shell environment (bash, zsh, etc.)","CCPM commands installed and in PATH","GitHub repository initialized with .claude/ directory","GitHub API token for Issue creation and updates"],"input_types":["Command-line arguments","PRD/Epic/Task specifications (via stdin or files)","GitHub Issue metadata"],"output_types":["GitHub Issues (created or updated)",".claude/ directory updates","Command output (status, errors, next steps)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_11","uri":"capability://memory.knowledge.agent.context.window.optimization.through.strategic.delegation","name":"agent context window optimization through strategic delegation","description":"Optimizes context window usage by delegating implementation details to specialized agents while keeping the main orchestration thread clean and strategic. The main thread maintains oversight of Epic progress without drowning in code details; each agent handles isolated context for its Task. This prevents context window exhaustion that typically occurs when a single agent tries to manage multiple files and implementation details simultaneously.","intents":["I want to prevent context window exhaustion in long-running projects","I need the main orchestration thread to stay strategic without implementation details","I want agents to focus on their Task without context pollution from other Tasks","I need to maximize context window efficiency across multiple agents"],"best_for":["large projects with multiple Tasks that would exceed single agent context","teams using multiple agents where context isolation is critical","workflows where context window exhaustion is a known problem"],"limitations":["Strategic oversight is limited to what fits in main thread context; complex Epics may still exceed limits","Delegation requires clear Task boundaries; overlapping Tasks may still cause context pollution","No automatic context window monitoring; developers must manually track usage","Context optimization is static; cannot adapt based on runtime context usage","No cross-agent context sharing; agents cannot reference each other's work directly"],"requires":["Clear Task boundaries that allow independent execution","Specialized agent roles with isolated context strategies","Main orchestration thread that stays strategic (not implementation-focused)","Monitoring of context window usage per agent"],"input_types":["Epic specification (high-level)","Task specifications (implementation-level)","Agent role and context strategy"],"output_types":["Agent context windows (isolated per Task)","Main thread context (strategic overview)","Context usage metrics"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_2","uri":"capability://memory.knowledge.github.issues.based.task.coordination.and.state.management","name":"github issues-based task coordination and state management","description":"Uses GitHub Issues as the distributed database and coordination layer for all project state: PRDs, Epics, Tasks, and agent assignments. Each Issue contains structured metadata (labels, assignees, linked issues) that agents read to understand task context and dependencies. Synchronization between local .claude/ directory and GitHub Issues enables team collaboration while maintaining local development efficiency through bidirectional updates.","intents":["I want a single source of truth for all project state that agents can query","I need to coordinate multiple agents through GitHub without custom databases","I want team members to see agent progress and task status in GitHub","I need to track dependencies between Epics and Tasks through GitHub relationships"],"best_for":["teams already using GitHub for version control","projects where GitHub Issues are the natural collaboration surface","workflows requiring visibility into agent progress for non-technical stakeholders"],"limitations":["GitHub API rate limits (60 requests/hour unauthenticated, 5000/hour authenticated) constrain polling frequency","Issue metadata is limited to labels, assignees, and linked issues — no custom fields without GitHub Projects","Synchronization is eventually consistent; local .claude/ state may lag GitHub by seconds to minutes","No built-in conflict resolution if local state and GitHub Issues diverge","Requires GitHub authentication; cannot work with private repositories without credentials"],"requires":["GitHub repository with Issues enabled","GitHub API token with repo scope","Network connectivity to GitHub API","Polling mechanism or webhook handler for sync (not built-in)"],"input_types":["GitHub Issue (Epic or Task)","Issue labels and metadata","Issue relationships (linked issues, parent/child)"],"output_types":["Local .claude/ directory state","GitHub Issue updates (status, assignee, labels)","Structured task metadata for agent consumption"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_3","uri":"capability://planning.reasoning.specialized.agent.role.deployment.and.task.assignment","name":"specialized agent role deployment and task assignment","description":"Deploys different agent types (Parallel Worker, Test Runner, Code Reviewer) based on task requirements, with each agent type optimized for specific work patterns. Agents are assigned to GitHub Issues through labels and metadata, and the system routes tasks to the appropriate agent based on task type (implementation, testing, review). Each agent type has its own context strategy and execution model optimized for its domain.","intents":["I want different agents to handle implementation, testing, and code review without manual routing","I need agents specialized for different task types to work more efficiently","I want to assign agents to tasks through GitHub metadata without custom configuration","I need agents to understand their role and constraints based on task type"],"best_for":["projects with distinct implementation, testing, and review phases","teams wanting to specialize agent behavior by task type","workflows where different agents need different context strategies"],"limitations":["Agent specialization is template-based; adding new agent types requires modifying system configuration","No dynamic agent selection based on task complexity or runtime conditions","Agent role assignments are static per task; cannot reassign mid-execution","No built-in load balancing across multiple instances of the same agent type","Agent context strategies are hardcoded; cannot adapt based on task characteristics"],"requires":["Agent templates defined in .claude/agents/ directory","GitHub labels matching agent types (e.g., 'type:implementation', 'type:test')","Claude API access for each agent instance","Task metadata in GitHub Issues (labels, description)"],"input_types":["GitHub Issue with task type label","Task description and acceptance criteria","Agent role specification"],"output_types":["Agent execution plan","Code changes or test results","Review feedback or approval"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_4","uri":"capability://planning.reasoning.epic.decomposition.into.parallel.tasks.with.dependency.tracking","name":"epic decomposition into parallel tasks with dependency tracking","description":"Decomposes Epics into multiple independent Tasks that can execute in parallel, with explicit dependency tracking through GitHub Issue relationships. The system identifies task boundaries that allow parallelization while respecting dependencies (e.g., database schema tasks must complete before ORM tasks). Uses GitHub linked issues to represent dependencies, enabling agents to understand task ordering and blocking relationships.","intents":["I want to break down large features into parallel work streams automatically","I need to identify which tasks can run in parallel and which have dependencies","I want agents to understand task ordering and blocking relationships","I need to maximize parallelism while respecting technical dependencies"],"best_for":["large features that naturally decompose into independent components","teams with multiple agents that can work in parallel","projects where task parallelization significantly reduces time-to-delivery"],"limitations":["Decomposition is manual or agent-assisted; no automatic dependency inference from code","Dependency tracking is limited to GitHub Issue relationships; no semantic understanding of code dependencies","Cannot detect hidden dependencies (e.g., two tasks modifying the same file)","Parallelism is logical; actual execution still depends on agent availability and API rate limits","No dynamic reordering if dependencies change mid-execution"],"requires":["Epic specification in GitHub Issue with clear scope","Manual or agent-assisted task decomposition","GitHub Issue linking for dependency representation","Clear task boundaries that allow independent execution"],"input_types":["Epic specification (GitHub Issue)","Feature requirements and acceptance criteria","Technical constraints and dependencies"],"output_types":["Task Issues (GitHub Issues)","Dependency graph (GitHub linked issues)","Task assignment to agents"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_5","uri":"capability://memory.knowledge.context.aware.agent.prompting.with.task.specific.constraints","name":"context-aware agent prompting with task-specific constraints","description":"Generates agent prompts that include task specification, acceptance criteria, relevant code context, and role-specific constraints (e.g., 'do not modify database schema' for ORM implementation). Prompts are constructed from GitHub Issue metadata, linked code files, and agent role templates, ensuring agents have sufficient context without context window pollution. Uses a context-preservation strategy where implementation details are delegated to specialized agents while the main thread stays strategic.","intents":["I want agents to have enough context to complete tasks without drowning in code","I need to constrain agent behavior through role-specific rules and boundaries","I want agents to understand task acceptance criteria and success conditions","I need to prevent agents from modifying out-of-scope files or systems"],"best_for":["projects with complex codebases where context selection is critical","workflows requiring strict scope boundaries for agent execution","teams using multiple agents that need different context strategies"],"limitations":["Context selection is heuristic-based; may include irrelevant code or miss critical dependencies","Constraints are soft (in prompt); agents can violate them if they choose","No automatic detection of constraint violations; requires post-execution review","Context window limits still apply; large tasks may exceed token budgets","Prompt engineering is manual; no adaptive prompting based on agent performance"],"requires":["GitHub Issue with task specification and acceptance criteria","Agent role template with constraints and context strategy","Relevant code files linked or referenced in task","Claude API with sufficient token budget for context + generation"],"input_types":["GitHub Issue (Task)","Agent role specification","Code context (files, functions, classes)","Acceptance criteria and constraints"],"output_types":["Agent prompt (text)","Structured task context (JSON or markdown)","Constraint specification"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_6","uri":"capability://automation.workflow.automated.testing.and.validation.within.agent.workflow","name":"automated testing and validation within agent workflow","description":"Integrates a Test Runner agent that executes tests within the task workflow, validating code changes against acceptance criteria before merging. Tests are defined in the task specification and executed in the isolated worktree, with results reported back to GitHub Issues. The system treats testing as a first-class workflow phase, not an afterthought, with dedicated agent role and context strategy optimized for test execution and debugging.","intents":["I want agents to validate their own code changes through automated tests","I need test results to be visible in GitHub Issues for team review","I want to prevent broken code from merging to main branch","I need agents to debug test failures and iterate until tests pass"],"best_for":["projects with comprehensive test suites","workflows requiring automated validation before merge","teams wanting agents to own test quality, not just code generation"],"limitations":["Test execution is limited to tests defined in task specification; cannot discover tests automatically","Test failures require agent debugging; no automatic root cause analysis","Test environment must be available in worktree; integration tests may fail due to missing services","Test execution time adds latency to task completion","No test coverage reporting or quality gates beyond pass/fail"],"requires":["Test suite defined in project (unit tests, integration tests)","Test command specified in task or agent configuration","Test environment available in worktree (dependencies, fixtures)","Test Runner agent configured with test execution role"],"input_types":["Code changes in worktree","Test specification (test files, test command)","Acceptance criteria from GitHub Issue"],"output_types":["Test execution results (pass/fail)","Test output and logs","GitHub Issue comment with test results"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_7","uri":"capability://code.generation.editing.code.review.integration.with.specialized.review.agent","name":"code review integration with specialized review agent","description":"Deploys a Code Review agent that analyzes code changes against acceptance criteria, architectural patterns, and code quality standards before merge. The review agent operates on the completed worktree, examining diffs and providing structured feedback through GitHub Issues. Review is treated as a distinct workflow phase with its own agent role, context strategy, and success criteria, enabling systematic code quality enforcement.","intents":["I want automated code review before human review to catch obvious issues","I need review feedback to be structured and tied to acceptance criteria","I want to enforce architectural patterns and code quality standards","I need review results visible in GitHub Issues for team discussion"],"best_for":["projects with defined code quality standards and architectural patterns","teams wanting to reduce manual review burden through automated pre-review","workflows where code review is a bottleneck"],"limitations":["Review agent cannot understand domain-specific quality criteria not in acceptance criteria","Review feedback is suggestions, not enforcement; agents can ignore feedback","No integration with linters or static analysis tools; review is semantic only","Review agent may miss subtle architectural violations or design issues","No learning from previous reviews; each review starts fresh"],"requires":["Acceptance criteria in GitHub Issue specifying quality standards","Code Review agent configured with review role and standards","Completed code changes in worktree","Architectural patterns or style guide accessible to review agent"],"input_types":["Code diff (changes in worktree)","Acceptance criteria from GitHub Issue","Architectural patterns or style guide","Previous review feedback (optional)"],"output_types":["Review feedback (structured comments)","GitHub Issue comments with review results","Approval or rejection decision"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_8","uri":"capability://memory.knowledge.local.claude.directory.state.management.and.synchronization","name":"local .claude/ directory state management and synchronization","description":"Maintains a local .claude/ directory structure that mirrors GitHub Issues state, enabling offline access and fast agent queries without repeated API calls. The directory contains PRDs, Epics, Tasks, agent configurations, and context files organized hierarchically. Synchronization between local state and GitHub Issues is bidirectional: local changes are pushed to GitHub, and GitHub updates are pulled locally, with conflict resolution through timestamps and manual intervention.","intents":["I want agents to query task state without hitting GitHub API rate limits","I need offline access to project state when GitHub is unavailable","I want to version control project metadata alongside code","I need fast local access to task specifications and context"],"best_for":["projects with frequent agent queries that would hit API rate limits","teams wanting to version control project metadata in Git","workflows requiring offline agent execution"],"limitations":["Local state can diverge from GitHub if sync fails or is delayed","No automatic conflict resolution; manual intervention required if local and GitHub state conflict","Sync is eventually consistent; agents may see stale state for seconds to minutes","Directory structure is convention-based; no schema validation","No built-in garbage collection; old state files accumulate unless manually cleaned"],"requires":[".claude/ directory initialized in project root","Git repository for version control of .claude/ directory","Sync mechanism (polling, webhooks, or manual) to keep state in sync","Write access to .claude/ directory for sync process"],"input_types":["GitHub Issues (Epics, Tasks)","Local .claude/ files (markdown, JSON)","Sync metadata (timestamps, hashes)"],"output_types":[".claude/ directory structure","Local state files (PRD, Epic, Task markdown)","Sync status and conflict reports"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-automazeio--ccpm__cap_9","uri":"capability://planning.reasoning.prd.to.epic.to.task.hierarchical.decomposition.with.traceability","name":"prd-to-epic-to-task hierarchical decomposition with traceability","description":"Implements a three-level hierarchical decomposition where PRDs are decomposed into Epics, Epics into Tasks, with explicit parent-child relationships maintained through GitHub Issue linking. Each level has specific artifacts and success criteria: PRDs define product vision, Epics define feature scope, Tasks define implementation work. Traceability is maintained through linked issues, enabling navigation from code back to original PRD requirement.","intents":["I want to trace any code change back to the original product requirement","I need to understand how features decompose into implementation work","I want to validate that all PRD requirements are covered by Tasks","I need to communicate feature scope to stakeholders through Epics"],"best_for":["projects requiring audit trails and requirement traceability","teams with non-technical stakeholders who need to understand feature scope","regulated industries where traceability is mandatory"],"limitations":["Decomposition is manual or agent-assisted; no automatic inference from code","Traceability is only as good as the linking discipline; broken links lose traceability","No validation that all PRD requirements are covered by Tasks","Decomposition changes require manual updates to Issue links","No impact analysis if PRD requirements change mid-project"],"requires":["PRD document in .claude/prd/ directory","GitHub Issues for Epics and Tasks","GitHub Issue linking to represent parent-child relationships","Discipline to maintain links as requirements change"],"input_types":["PRD markdown document","Epic specification (GitHub Issue)","Task specification (GitHub Issue)"],"output_types":["GitHub Issue hierarchy (PRD → Epic → Task)","Traceability links (GitHub linked issues)","Traceability report (code → Task → Epic → PRD)"],"categories":["planning-reasoning","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":48,"verified":false,"data_access_risk":"high","permissions":["GitHub repository with Issues enabled","Git with worktree support (Git 2.15+)","Claude API access (via Claude Code or direct API)",".claude/ directory structure initialized in project root","Git 2.15+ with worktree support","Sufficient disk space for N worktrees (each ~copy of codebase)","Multiple Claude API keys or rate-limit headroom for parallel requests","GitHub repository with write access for branch creation","Shell environment (bash, zsh, etc.)","CCPM commands installed and in PATH"],"failure_modes":["Requires strict adherence to five-phase discipline — cannot skip phases without breaking workflow integrity","PRD documents must be manually written; system does not auto-generate requirements from user stories","Phase transitions are sequential; cannot parallelize PRD→Epic→Task decomposition steps","Workflow enforcement is convention-based through commands, not cryptographically enforced","Worktree creation adds ~500ms overhead per agent spawn","Merge conflicts still possible if agents modify overlapping files; requires manual resolution","No automatic conflict detection — relies on Git merge to surface issues","Worktree cleanup must be manual or scripted; no built-in garbage collection","Maximum practical parallelism limited by API rate limits and token budgets per agent","Commands are shell-based; requires command-line familiarity","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.6389737875089658,"quality":0.49,"ecosystem":0.5800000000000001,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.549Z","last_scraped_at":"2026-05-03T13:58:34.540Z","last_commit":"2026-03-18T12:15:24Z"},"community":{"stars":8061,"forks":816,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=automazeio--ccpm","compare_url":"https://unfragile.ai/compare?artifact=automazeio--ccpm"}},"signature":"KAUTJZYZU7u8cdLamZAyKyJ1ISlU/cBorx+noqWqORmBknZu6km4t2CZswF0VtBelBVwIiHpMPNY3t+kPVBQCg==","signedAt":"2026-06-20T03:09:21.418Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/automazeio--ccpm","artifact":"https://unfragile.ai/automazeio--ccpm","verify":"https://unfragile.ai/api/v1/verify?slug=automazeio--ccpm","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}