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reverse-engineering

To reverse-engineer code into a spec: extract behavior and domain logic — WHAT and WHY, not HOW.

Quality

65%

Does it follow best practices?

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Passed

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tessl review fix ./instructions/r2/core/skills/reverse-engineering/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%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 content is a strong judgment-focused skill: concrete, example-driven heuristics that assume Claude's intelligence without padding. Its main weaknesses are noticeable duplication between core_concepts and pitfalls, and the lack of an explicitly sequenced workflow with validation checkpoints.

Suggestions

Deduplicate content: merge the four near-identical concept/pitfall pairs (duplicate terminology, dead code, implicit state machines, concrete detail trap) so each idea appears once, cutting the pitfalls section to only novel failure modes.

Add an explicit ordered workflow (e.g., 1. Scope and map the territory, 2. Apply extraction tests per code area, 3. Consolidate and normalize terminology, 4. Validate the spec with developers and stakeholders) so the sequence currently scattered across rules and concepts becomes a single checklist.

Clarify or drop cryptic rules such as 'Maintain ideas, hooks, meaning, strategy, tricks, and similar' and fix the garbled 'Why it is there this way?' test in concept 5.

DimensionReasoningScore

Conciseness

The body avoids explaining concepts Claude already knows and uses dense, high-value heuristics, but there is real duplication: duplicate terminology (concept 13 vs pitfall 2), dead code (16 vs 3), implicit state machines (10 vs 5), and the concrete detail trap (7 vs 6) each appear twice in near-identical wording. This is more than minor trimming, so it sits at 3 rather than 4.

3 / 5

Actionability

The heuristics are unusually concrete for a judgment skill, with real mapping examples (nullable 'reminded_at'/'feedback_id' columns to named states, 'requests.post(...)' vs 'Notify the interviewer', 'candidate_id: Integer' becoming 'candidacy: Candidacy'). A few rules are cryptic ('Maintain ideas, hooks, meaning, strategy, tricks') with no example, keeping it below 5.

4 / 5

Workflow Clarity

A rough sequence is discernible (scope first in the rules, 'Map the territory before extracting anything' in concept 9, two-direction validation in concept 21), but the steps are scattered across prose rather than presented as an ordered workflow, and validation checkpoints are implicit rather than explicit. Not 2 because the ordering cues are consistently stated; not 4 because no sequenced procedure with checkpoints is laid out.

3 / 5

Progressive Disclosure

A self-contained single file with no bundle files, organized into clearly labeled sections (role, core_concepts, rules, pitfalls). At ~72 lines with 21 concepts plus pitfalls all inline, it exceeds the under-50-line simple-skill case, so organization is good but not maximal; 4 fits 'good structure with minor gaps'.

4 / 5

Total

14

/

20

Passed

Description

53%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.

The description communicates a clear, well-scoped 'what' with a memorable WHAT/WHY-vs-HOW framing, but it completely lacks 'when to use' trigger guidance, which both caps completeness and weakens trigger-term quality. Adding a 'Use when...' clause would lift the two weakest dimensions.

Suggestions

Append a trigger clause such as 'Use when asked to understand, document, or derive requirements/specs from existing code, or when reconstructing what legacy code is supposed to do.'

Enumerate the concrete actions more fully (e.g., 'extract behavior, identify implicit state machines, consolidate scattered business rules, separate domain logic from implementation detail') to raise specificity beyond 1-2 actions.

Add natural user-phrase synonyms like 'understand this codebase', 'document legacy code', or 'write a spec from code' to improve trigger-term coverage.

DimensionReasoningScore

Specificity

Names the domain ('reverse-engineer code into a spec') and 1-2 concrete actions ('extract behavior and domain logic'), but does not comprehensively enumerate what the skill does. It stays at the level of 'Processes PDF files and extracts content' rather than listing several specific actions.

3 / 5

Completeness

Answers 'what' clearly (extract behavior and domain logic into a spec, WHAT/WHY not HOW) but has no 'when' clause or equivalent trigger guidance, which caps completeness at 3 per the rubric guidelines. Not score 4 because 'when' is entirely absent rather than merely implicit.

3 / 5

Trigger Term Quality

Contains relevant keywords ('reverse-engineer', 'code', 'spec', 'domain logic'), but misses the natural phrases a user would say such as 'understand this codebase', 'document legacy code', or 'extract requirements'. Coverage is relevant but thin on synonyms and variations.

3 / 5

Distinctiveness Conflict Risk

'Reverse-engineer code into a spec' carves out a mostly distinct niche with minor overlap risk against adjacent skills (code review, refactoring, documentation). Not 5 because the absence of 'when' guidance leaves boundary with adjacent code-analysis skills less sharply drawn.

4 / 5

Total

13

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

griddynamics/rosetta

Path

instructions/r2/core/skills/reverse-engineering/SKILL.md

Reviewed

Table of Contents

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