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learn-reverse-engineering

Focused interactive tutor for the Reverse Engineering path in AI Engineering from Scratch. Start or resume this route when a learner wants to read a compiled program: file formats, disassembly, control flow, lifting, evidence, proof, calling conventions, compiler idioms, linking, types, debugging, bytecode, diffing, symbolic execution, and AI-assisted analysis. Teaches one lesson per invocation and records evidence in REVERSE-ENGINEERING-LEARNING.md.

Quality

90%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is learn-reverse-engineering in rohitg00/ai-engineering-from-scratch

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a tight operational protocol: concrete commands, paths, and response formats, with strong validation gating on every status change and a complete resume/create flow for learner progress. The only structural critique is that the per-lesson checkpoint list and progress template duplicate manifest data inline rather than staying a lean overview.

DimensionReasoningScore

Conciseness

The body never explains concepts Claude already knows (no "what is ELF" padding) and stays operational throughout — exact statuses, paths, and formats. Minor trimmable spots (the host invocation table and the "Lesson screen" section) keep it at anchor 4 rather than 5, but nothing rises to the unnecessary explanation of anchor 3.

4 / 5

Actionability

Guidance is fully executable: exact source paths ("learning-paths/reverse-engineering.json"), a copy-paste fetch URL template, concrete preflight checks ("python3 --version reports 3.10 or later"), an exact quiz format ("Reply with one letter: <A|B|C|D>."), and a complete copy-paste-ready progress-file template. Lab commands are appropriately delegated to the lesson files the tutor is instructed to read.

5 / 5

Workflow Clarity

The process is clearly sequenced (preflight → locate/create progress → 8-step teach loop → close) with explicit validation gates and feedback loops: "Never mark a prerequisite complete by assumption", "Mark the row Done only after the checkpoint and quiz are complete", "A fluent explanation does not replace an observed output", and Pending-lab fallback handling. This matches the anchor-5 pattern of sequence plus explicit validation and error recovery.

5 / 5

Progressive Disclosure

The body is well-sectioned with clear navigation, and external references (the manifest, "manuals/reverse-engineering-101/") are explicitly pathed and one level deep. It falls short of anchor 5 because the 14-item checkpoint list and the full progress table are inlined even though the manifest is declared the source of truth — content that could be offloaded or trimmed to keep SKILL.md a pure overview.

4 / 5

Total

18

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it states a clear niche, gives an explicit and concrete when-clause, and lists several concrete actions plus a rich set of natural topic keywords. Its only weakness is missing a few common synonyms (decompile, binary analysis) that would push trigger coverage to comprehensive.

DimensionReasoningScore

Specificity

Concrete actions include "Start or resume this route", "Teaches one lesson per invocation", and "records evidence in REVERSE-ENGINEERING-LEARNING.md" — several specific actions with minor gaps. It sits above anchor 3 (only 1-2 actions) but below anchor 5 because the long colon list ("file formats, disassembly, control flow, lifting...") is domain enumeration rather than distinct action coverage.

4 / 5

Completeness

Both parts are explicit: what — "Focused interactive tutor for the Reverse Engineering path... Teaches one lesson per invocation and records evidence in REVERSE-ENGINEERING-LEARNING.md"; when — "Start or resume this route when a learner wants to read a compiled program". The when-clause is concrete and specific, matching anchor 5 rather than anchor 4's generic "Use when working with PDF files" style.

5 / 5

Trigger Term Quality

Good natural keyword coverage: "reverse engineering", "disassembly", "compiled program", "debugging", "bytecode", "symbolic execution", "diffing" are phrases a learner would plausibly say. Not anchor 5 because common synonyms like "decompile/decompilation", "binary analysis", "assembly", or "hex" are absent.

4 / 5

Distinctiveness Conflict Risk

"the Reverse Engineering path in AI Engineering from Scratch" names a clear niche, and the trigger ("when a learner wants to read a compiled program") is scoped and unlikely to fire for unrelated skills. Overlap risk from generic words like "debugging" is minimal, fitting anchor 5; it is clearly more distinct than anchor 4's "mostly distinct, minor overlap" example.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

rohitg00/ai-engineering-from-scratch

Path

.claude/skills/learn-reverse-engineering/SKILL.md

Reviewed

Table of Contents

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