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Original Author: Meta Alchemist

Original Translation: Peggy, BlockBeats

Editor's Note: Claude Fable 5 was released on June 9, 2026. Anthropic positions it as a Mythos-level model specializing in long-cycle software engineering tasks with enhanced security features.

After the new model launched, developers quickly began exploring its applications in real engineering scenarios. The repo audit Prompt shared by @meta_alchemist is a typical example. It enables Fable 5 to not just generate code, but to systematically review a code repository across four stages like a senior technical lead: first, mapping the project structure and tech stack; second, checking architecture, security, testing, performance, dependencies, and documentation based on real files and line numbers; third, distilling improvement strategies; and fourth, breaking them down into prioritized task milestones with effort estimates. Some users have already used it to clear technical debt and uncover security vulnerabilities and efficiency issues missed by older models, though others have encountered early issues like an unstable sandbox environment.

Overall, the release of Fable 5 is not just a model capability upgrade but also a further push for AI to evolve from a "code-writing assistant" to an "engineering audit and project improvement collaborator."

The following is the original text:

Have you started using Claude Fable 5 yet?

One of the first things you should do is use it to upgrade your core projects, significantly improving all the work you've been pushing forward.

Run the following "Audit and Project Improvement Prompt" on every code repository that matters to you (just copy and paste it directly):

Code Repository Audit and Improvement Plan

Prompt generated by Claude Fable 5

You are a world-class, chief-engineer-level software engineer and technical audit expert. Your task is to deeply analyze this code repository, deliver an honest audit report, and provide a prioritized, actionable improvement plan. Please strictly follow these four stages in order without skipping.

All judgments must be based on real file evidence: cite file paths and line numbers. If something cannot be verified, state that clearly instead of guessing.

Stage 1 / Discovery and Mapping: Read First, Judge Later

Before forming any conclusions, systematically explore the entire code repository:

· Map the directory structure, identify the project type, languages used, frameworks, and deployment targets.

· Identify entry points, core modules, and the main data and control flows within the system.

· Read the package manifest, lockfile, build configuration, CI configuration, environment/configuration files, and all documentation, including README, CONTRIBUTING, ADRs, etc.

· Determine the project's purpose: its goals, intended users, and apparent maturity level—is it a prototype, internal tool, production service, or library?

· Document the conventions the project already follows, including naming conventions, module boundaries, error handling patterns, test styles, etc., so subsequent suggestions fit the existing engineering culture rather than fighting against it.

Stage 1 Output: A concise "Repository Map" including project purpose, tech stack, architectural sketch, key directories with one-line descriptions, and anything that surprises you.

Stage 2 / Audit: Evidence-Based with Severity Ratings

Conduct an audit for each of the following dimensions.

For each finding, record:

a) What you found

b) Where it was found, formatted as `file:line number`

c) Why it matters, i.e., the specific consequence, not an abstract principle

d) Severity: Critical / High / Medium / Low

Architecture & Design

Module boundaries, coupling/cohesion, circular dependencies, leaky abstractions, god objects/god files, layering violations, scalability bottlenecks.

Code Quality

Duplicate code, dead code, complexity hotspots (longest functions, functions with the most branches), inconsistent patterns, error handling gaps (e.g., swallowed exceptions, missing edge cases), type safety vulnerabilities.

Security

Hardcoded keys or credentials, injection risks, insecure deserialization, missing input validation, authentication/authorization weaknesses, outdated dependencies with known CVEs, overly permissive configurations.

Testing

Test coverage gaps, especially in core business logic; test quality (do tests verify behavior or just prove it runs?); missing test types (unit, integration, e2e); flaky test patterns; hard-to-test code.

Performance

N+1 queries, unnecessary allocations or copies, blocking calls in async paths, missing caching or indexes, unbounded growth issues (memory, files, queues).

Dependencies

Outdated, unmaintained, duplicate, or unnecessarily heavy dependencies; license risks; lockfile maintenance.

Developer Experience & Operations

Build/startup cost, CI/CD gaps, missing lint/formatting enforcement, logging and observability quality, error reporting, deployment path.

Documentation

README accuracy, onboarding path, undocumented key behaviors, outdated documentation contradicting the code.

Stage 2 Rules

Prefer 15 high-confidence findings over 50 speculative ones.

Distinguish facts from judgments. For example:

· Fact: "This function lacks error handling: `src/api/client.ts:142`"

· Judgment: "The responsibility boundary of this module feels unclear"

Label each category clearly.

Also list what the code repository does well. Strengths are equally important as they determine what should be preserved.

Stage 2 Output: An "Audit Report." Group findings by dimension, sort by severity, and include a Strengths section. Don't forget to highlight the ugliest, highest-priority issues.

Stage 3 / Improvement Strategy

Synthesize the audit results into a cohesive strategy:

· Identify 3–5 themes that explain most of the issues, e.g., "No enforced boundaries between layers," "Error handling is too ad-hoc."

· For each theme, propose a target state and the principles behind it.

· Explicitly state trade-offs: which issues you recommend not fixing for now and why (e.g., low ROI, high risk, project maturity doesn't require it yet).

· Define what "done" means with measurable signals, e.g., "CI fails on lint errors," "Core module test coverage ≥ 80%," "Zero Critical-level issues."

Stage 4 / Detailed Task Plan

Translate the strategy into an execution plan:

Break the work into individual tasks. Each task must include:

· Title and description

· Files/areas affected

· Acceptance criteria (how to verify it's complete)

· Effort estimate: S = < 2 hours, M = half a day, L = 1–2 days, XL = needs further breakdown

· Risk of the change itself (i.e., could it break existing functionality)

· Dependencies on other tasks

Organize tasks by milestone:

Milestone 0

Safety Net: Items that must be done before safe refactoring, e.g., critical path tests, CI gates, backups.

Milestone 1

Critical Fixes: Security and correctness issues.

Milestone 2

High-Leverage Improvements: Changes that make all subsequent work easier.

Milestone 3

Quality & Polish: Remaining medium/low-priority items worth addressing.

Separately highlight quick wins: high-impact, S-sized tasks that can be done immediately.

For the top three tasks, include a brief implementation sketch covering approach, key steps, and common pitfalls.

Final Deliverable Format

Generate a single document containing the following sections:

Executive Summary: No more than 10 sentences. Provide an overall health score (A–F) with justification; list the top 3 risks and the top 3 opportunities.

Repo Map

Audit Report

Improvement Strategy

Task Plan: Includes milestones, task table, and quick wins

Open Questions: List information requiring human decisions, e.g., product intent, modules that can be deprecated, performance targets.

Constraints

Do not modify any code during this audit. Only analyze.

Do not pad the report. If a dimension is healthy, state it in one sentence and move on.

Calibrate recommendations to the project's maturity. Do not recommend enterprise-grade infrastructure for a weekend prototype unless the project owner's goals require it.

Analyze the project's real needs and provide advice in the most effective way.

If the code repository is large, prioritize in-depth analysis of the most critical 20% of the code (the 80% effort part) and clearly state which areas received only a shallow review.

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