parcadei

Coordinate investigation, fixes, tests, and commits for bugs, Claude Code hooks, dependency errors, and pull request feedback. Route work to specialized skills and agents, with human review checkpoints, diagnosis-only options, and a handoff record.

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• Investigate and fix a bug
• Diagnose a Claude Code hook that does not run
• Resolve package or import errors

Route requests to commit, push, or save Git changes through a dedicated /commit skill. The workflow removes Claude attribution, records attempted approaches in reasoning.md, clears build attempts, and pushes changes when requested.

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• Saving changes through the designated commit workflow
• Preserving attempted approaches alongside a commit
• Removing Claude attribution from commit messages

Build Python agents with Agentica SDK using function decorators or agent instances. Examples cover conversation memory, external tools, MCP connections for tool access, multi-agent coordination, typed results, and logging to help implement and debug agent behavior.

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• Add agent behavior to existing Python functions
• Build a chatbot that remembers conversation history
• Connect agents to external tools through MCP

Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.

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• Clarifying instructions for reading and editing files
• Dividing research among multiple agents
• Passing findings and plans between agents

Find and replace code using syntax patterns with ast-grep. Search for function calls, imports, and definitions while excluding matches inside strings or comments, then preview proposed replacements before applying changes across selected files or directories.

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• Finding function calls or import statements
• Replacing logging calls across a codebase
• Searching selected directories or file types

Inspect Claude Code execution traces in Braintrust, including tool calls and token usage. The guide explains event hooks, troubleshooting missing records, and matching separate parent and sub-agent traces using timestamps and metadata.

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• Investigating missing execution traces
• Reviewing tool calls and token usage
• Matching parent and sub-agent execution records

Find unused functions through static analysis, which examines code without running it. Scan a project or directory, choose a language, and exclude designated entry points to get a list of functions with file locations.

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• Listing unused functions across a project
• Checking a specific directory before cleanup
• Excluding entry points and handlers from analysis

Guide implementations that pass session and trace identifiers explicitly between processes and asynchronous steps. It covers storing IDs, using full UUIDs, and separating identifier types to prevent results from being attributed to the wrong session.

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• Passing session IDs to child processes
• Reviewing identifiers across asynchronous steps
• Keeping session and trace IDs distinct

Standardize Python scripts that call MCP tools, which connect an agent to external capabilities. The rules cover command-line parameters, usage documentation, tool names, error messages, and output that Claude can process.

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• Creating scripts that call MCP tools
• Replacing hardcoded settings with command-line arguments
• Reviewing script documentation, errors, and output

Search GitHub code, repositories, issues, and pull requests through MCP, a connection to external tools. Use GitHub search syntax and owner or repository filters to find implementation examples, bug reports, and project information.

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• Find implementation examples across repositories
• Find critical bug reports
• Find related pull requests

Design software that keeps working with reduced features when an optional service is unavailable. The skill provides patterns for early availability checks, cached results, and messages explaining what is missing, which features are affected, and how to restore them.

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• Keeping available features running during an optional service outage
• Writing messages with clear service setup steps
• Caching availability checks to avoid repeated requests

Discover the tools, workflows, specialist agents, and hooks available in a configured workspace. Interactive guidance and topic-specific commands help you choose relevant capabilities, inspect usage examples, and understand customization options.

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• Find workspace capabilities that match a task
• Browse development workflows and specialist agents
• Understand active hooks and their roles

Provides a reference for building Claude Code hooks, scripts or model checks triggered by events. Covers input and output formats, registration, testing, and debugging for tasks such as blocking tool calls, adding context, and checking tests before stopping.

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• Create a hook that blocks edits to protected files
• Format files automatically after edits
• Add Git context when submitting a prompt

Design fallback and repair paths to be idempotent, meaning repeated runs leave the same result. The skill outlines checks before writing, atomic file updates, and reconciliation practices to avoid overwrite conflicts and repeated repair loops.

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• Adding fallback paths that write only when values are missing
• Reviewing repair steps that may run repeatedly
• Preventing file overwrite conflicts between writers

Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.

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• Keeping long agent transcripts out of the main conversation
• Passing research and plans between agents through files
• Checking for stalled background agents

Retrieve web page content from a URL or search query through Firecrawl MCP. Export it as Markdown, HTML, or plain text, with support for extracting structured data from pages.

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• Collecting content from a specific web page
• Searching the web and retrieving page content
• Extracting structured data from web pages

Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.

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• Choose a coordination pattern for multiple agents
• Check pattern constructors and methods
• Implement custom coordination patterns

Carry out technical plans in verified stages, with automated checks followed by human review. The skill defines task delegation, progress tracking, and persistent handoff records so work can resume with the context needed for the next task.

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• Implementing a technical plan in verified stages
• Assigning separate agents to sequential tasks
• Resuming work from saved handoff records

Carry out approved technical plans in phases, checking success criteria and recording progress as work proceeds. Larger plans can use separate agents with saved handoff notes, while manual verification keeps users involved at phase boundaries.

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• Implementing an approved technical plan
• Checking results at each implementation phase
• Resuming work from unfinished plan items

Turn math requests into specific command-line instructions using pattern-based routing. It covers calculus, equations, unit conversion, geometry, logical proofs, and plotting, returning a command for the agent to execute with the corresponding math script.

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• Turning integration or differentiation requests into commands
• Finding commands for unit conversion or compatibility checks
• Routing geometry calculations and plotting requests

Implement one task from a larger development plan using test-driven development, where tests precede code. Record changes, decisions, test results, and blockers in a handoff document so the next agent can continue with the necessary context.

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• Implementing one task from a larger development plan
• Adding functionality by writing failing tests first
• Passing implementation details to the next agent

Guide agents to index files as soon as they are created, making them searchable for subsequent tasks. The skill describes write-triggered indexing and single-file updates instead of waiting for session-end batches or scheduled jobs.

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• Making handoff documents searchable immediately
• Triggering indexing when a file is written
• Reviewing indexing delays in downstream workflows

Choose LLM settings for theorem proving, code generation, and creative exploration. It provides examples for output limits and response variety, plus proof planning prompts and a method for generating multiple proof attempts and selecting the best candidate.

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• Choosing LLM settings for theorem proving
• Adjusting output settings for code generation
• Increasing response variety for creative exploration

Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.

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• Dividing implementation work among specialized agents
• Checking a plan against research before implementation
• Writing failing tests before implementing changes