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cloud-recon

Cloud infrastructure enumeration — AWS S3 buckets, Azure blob storage, GCP buckets, cloud metadata endpoints, IAM misconfigurations, CDN origin detection.

64

Quality

77%

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SecuritybySnyk

Critical

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tessl review fix ./packages/decepticon/decepticon/skills/standard/recon/cloud-recon/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

The content is highly actionable with concrete, copy-paste-ready commands and good progressive disclosure via two well-signaled reference files. It is held back by minor redundancy/verbosity and a workflow that lacks explicit validation checkpoints for batch operations.

Suggestions

Tighten conciseness by dropping the motivational intro sentence and removing the inline CNAME/header pattern duplication that already lives in references/cloud-ip-ranges.md, keeping only a brief pointer.

Add explicit validation checkpoints to the section 8 workflow — e.g., confirm a bucket actually exists before access testing, and verify enumerated findings before moving to documentation — to satisfy the validate→fix→retry expectation for batch enumeration.

Gate the batch for-loops with a quick existence/permission check (HTTP code branch) so destructive or write-oriented access tests only run after read enumeration succeeds.

DimensionReasoningScore

Conciseness

The body is mostly lean command references and tables, but the intro sentence "Modern organizations run hybrid infrastructure — cloud recon is essential for complete attack surface mapping" is motivational fluff, and the inline CNAME/header patterns in section 1 duplicate content already in references/cloud-ip-ranges.md. This fits "mostly efficient but could be tightened" rather than the score-3 bar where every token earns its place.

2 / 3

Actionability

The body is packed with concrete, executable guidance — `dig`, `curl` with specific endpoints, an inline python3 IP-range script, and for-loops with explicit bucket prefixes and `<target>` placeholders — making it copy-paste ready. It is not the score-2 level of pseudocode or incomplete guidance.

3 / 3

Workflow Clarity

Section 8 lays out a clear 8-step recon sequence, but there are no explicit validation checkpoints or validate→fix→retry feedback loops, and the batch bucket-enumeration loops lack validation gates. Per the rubric, missing validation for batch operations caps workflow clarity at 2; it is above 1 because the sequence is clear, but below 3 because checkpoints are absent.

2 / 3

Progressive Disclosure

The body clearly signals two real, one-level-deep references ("See references/cloud-ip-ranges.md…" and "See references/cloud-naming-patterns.md…"), both verified to exist with substantial content, and is organized into nine numbered sections with detail appropriately split into the reference files. This matches the anchor for a clear overview with well-signaled one-level-deep references.

3 / 3

Total

10

/

12

Passed

Description

82%

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 is specific, actionable, and well-differentiated within the cloud-recon niche, with natural trigger terms. Its main gap is the missing "Use when…" trigger guidance inside the description field itself, which leaves completeness capped.

Suggestions

Append a "Use when…" clause to the description field with explicit triggers (e.g., "Use when the user asks about cloud assets, exposed S3/Azure/GCP buckets, IAM misconfigurations, or origins behind a CDN") rather than relying on metadata.when_to_use.

Add a couple of common user phrasings (e.g., "find leaked buckets", "check for open cloud storage") to broaden natural trigger coverage beyond the current enumeration-oriented terms.

DimensionReasoningScore

Specificity

The description states a concrete action ("Cloud infrastructure enumeration") and enumerates multiple specific targets — "AWS S3 buckets, Azure blob storage, GCP buckets, cloud metadata endpoints, IAM misconfigurations, CDN origin detection" — matching the anchor for listing multiple specific concrete actions. It is well above the score-2 level of naming only a domain and some actions.

3 / 3

Completeness

The "what" is clearly answered (cloud infrastructure enumeration with concrete targets), but the description field contains no "Use when…" clause or equivalent explicit trigger guidance; per the rubric this caps completeness at 2. Explicit triggers do exist, but only in the separate metadata.when_to_use field, not in the description under evaluation.

2 / 3

Trigger Term Quality

Terms like "S3 buckets", "Azure blob storage", "GCP buckets", "IAM misconfigurations", and "CDN origin" are natural language a user doing cloud recon would actually say, giving good coverage rather than jargon-only or generic phrasing.

3 / 3

Distinctiveness Conflict Risk

The cloud-specific enumeration targets carve a clear niche that is unlikely to trigger for non-cloud skills, matching the anchor for a clear niche with distinct triggers. It is far more specific than the score-2 "could overlap" level.

3 / 3

Total

11

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
PurpleAILAB/Decepticon
Reviewed

Table of Contents

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