roasbeef/claude-files · Archived

agentic-code-reasoner

This skill enables deep, execution-free code analysis using the "Semi-Formal Reasoning" methodology.

First seen Mar 9, 2026

Installation

$ npx skills add roasbeef/claude-files --skill agentic-code-reasoner

Summary

  • This skill enables deep, execution-free code analysis using the "Semi-Formal Reasoning" methodology.
  • Use it for complex debugging, patch verification, or subtle logic questions where standard inspection might miss edge cases.
  • It requires the generation of a "Reasoning Certificate" verifying logic paths before delivering a conclusion.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 19
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,279 B
  • docs SUMMARY.md 364 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Agentic Code Reasoner

This skill implements the "Agentic Code Reasoning" framework, focusing on semi-formal reasoning. It bridges the gap between unstructured reasoning and fully formal verification by using structured reasoning templates that force explicit evidence for every claim.

When to Use

  • Patch Equivalence: Verifying if two code patches produce the same semantic outcomes without execution.
  • Fault Localization: Identifying the exact lines of buggy code given a failing test description.
  • Code Question Answering: Answering nuanced questions about project-specific logic, library semantics, and edge cases.
  • Pre-commit Review: Performing deep semantic analysis of changes to prevent regressions.

The Semi-Formal Protocol

To perform agentic code reasoning, follow this iterative protocol to generate a Reasoning Certificate.

Phase 1: Context & Premise Extraction

  • Goal: Establish a baseline of facts from the codebase.
  • Action: List all relevant function signatures, variable types, constants, and imported library behaviors involved.
  • Verification: Use grepsearch and readfile to ensure every premise is grounded in actual code.
  • Format:

- [Premise] Function <name> defined in <file> accepts <args> - [Premise] Global constant <MAX_RETRIES> is set to <value>

Phase 2: Symbolic Execution Trace

  • Goal: Mentally simulate execution paths for specific scenarios.
  • Action:

- Control Flow: Trace the path step-by-step (e.g., "Enter if block"). - Data Flow: Track the state of key variables (e.g., "x is now Tainted"). - Loop Analysis: For loops, explicitly trace "Iteration 0", "Iteration 1", and "Iteration N" to catch boundary errors.

  • Micro-Experiments: You MAY use runshellcommand to execute small, isolated scripts (e.g., python3 -c ...) to verify language semantics (e.g., regex behavior, float precision), but NEVER to run the project's own code or tests.
  • Interprocedurality: If a function is called, you MUST read its definition and include its trace as a sub-step.
  • Format:

1. [Trace Step 1] Entry point <function> called with <params>. 2. [Data Flow] Variable <user_input> is untrusted. 3. [Loop Analysis] Iteration 0: i=0, condition true. Iteration 1: ...

Phase 3: Property Verification & Divergence Analysis

  • Goal: Prove or disprove the target property (e.g., "is there a bug?", "are these equivalent?").
  • Action:

- For Bugs: Identify divergence points and generate Ranked Predictions (e.g., "Suspect #1: line 45 (80% confidence)"). - For Equivalence: Trace both versions and identify if the side effects or return values differ.

  • Self-Correction Loop:

- If a trace contradicts a premise (e.g., "Trace says X is null, Premise says X is safe"), STOP. - Backtrack: Re-verify the premise using readfile or grepsearch. - Refine: Update the premise or the trace with the new finding before proceeding.

Phase 4: Formal Conclusion

  • Goal: Provide the final verdict based strictly on the certificate.
  • Action: Summarize the findings, referencing specific Trace Steps or Claims from Phase 3.

Workflow Patterns

Refer to the specialized templates in references/reasoning_templates.md for specific tasks:

  • Patch Equivalence Verification Template
  • Fault Localization (Bug Hunter) Template
  • Deep Code Q&A Template

Guidelines

  • No Execution: This skill is for reasoning without running the code. Do not suggest running tests as a primary verification method.
  • Evidence-First: Never make a claim without a [Premise] or [Trace Step] supporting it.
  • Deep Context: If a trace hits a library function whose behavior is unknown, use grepsearch or webfetch to find the documentation or implementation.