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audit-context-building

Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.

39

Quality

37%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/audit-context-building/SKILL.md

The canonical home for this skill is audit-context-building in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

42%Scale 1-3

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

The skill demonstrates strong structural organization and good progressive disclosure with external references, but suffers significantly from verbosity—restating the same concepts multiple times and explaining abstract reasoning frameworks Claude already understands. Actionability is moderate: the checklists and thresholds provide concrete structure, but the lack of inline examples and reliance on abstract directives ('Apply First Principles') weakens practical guidance.

Suggestions

Cut sections 1, 3, 9, and 10 down to 2-3 lines total—they repeat the same 'pure context, no vulnerabilities' message at least 4 times. Consolidate into a single brief scope statement.

Include at least one concrete inline example showing a completed micro-analysis of a small function (even abbreviated), rather than deferring all examples to external files. This makes the expected output format immediately clear.

Remove the rationalizations table—Claude doesn't need motivational coaching about why thoroughness matters. Replace with a brief 'Common pitfalls' list if needed.

Define explicit transition criteria between phases (e.g., 'Move to Phase 3 when all public/external functions have completed micro-analysis and the completeness checklist is satisfied').

DimensionReasoningScore

Conciseness

Extremely verbose for what it communicates. Much of the content describes how Claude should 'think' and 'behave' in abstract terms Claude already understands. The rationalizations table, repeated behavioral descriptions across sections 1/3, and extensive non-goals/relationship sections add significant token overhead without proportional value. Many sections restate the same ideas (e.g., 'pure context building' is stated at least 4 times).

1 / 3

Actionability

The skill provides structured checklists and a clear microstructure format (Section 5.1), which gives concrete guidance on what to produce. However, there is no executable code, no concrete examples inline (the example is deferred to an external file), and much of the guidance remains at the level of abstract instruction ('Apply 5 Whys') rather than showing exactly what the output looks like. The quality thresholds in 5.4 are concrete and helpful.

2 / 3

Workflow Clarity

The three-phase workflow (Orientation → Granular Analysis → Global Understanding) is clearly sequenced, and the completeness checklist in 5.5 serves as a validation checkpoint. However, there are no explicit feedback loops for error recovery between phases, and the transitions between phases are implicit ('after sufficient micro-analysis') rather than having clear criteria for when to advance.

2 / 3

Progressive Disclosure

Content is well-structured with clear section hierarchy. Detailed examples and output requirements are appropriately deferred to external files (FUNCTION_MICRO_ANALYSIS_EXAMPLE.md, OUTPUT_REQUIREMENTS.md, COMPLETENESS_CHECKLIST.md) with clear descriptions of what each contains. References are one level deep and well-signaled.

3 / 3

Total

8

/

12

Passed

Description

32%Scale 1-3

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 conveys a general sense of purpose—deep code analysis for security and bug finding—but lacks concrete action verbs, explicit trigger guidance, and natural user keywords. It reads more like a marketing tagline ('ultra-granular') than a functional skill description, and the absence of a 'Use when...' clause significantly hurts its utility for skill selection.

Suggestions

Add an explicit 'Use when...' clause with trigger scenarios, e.g., 'Use when the user asks for a security audit, vulnerability scan, code review for bugs, or deep analysis of a codebase.'

List specific concrete actions the skill performs, e.g., 'Performs line-by-line code review, maps function call graphs, identifies security vulnerabilities (injection, XSS, buffer overflow), and traces data flow for bug detection.'

Include natural user keywords and file/language references, e.g., 'security review, find bugs, code audit, static analysis, vulnerability assessment' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (code analysis, vulnerability/bug finding) and mentions 'line-by-line code analysis' and 'build deep architectural context', but doesn't list multiple concrete actions—it's more of a high-level description of an approach than specific capabilities.

2 / 3

Completeness

Describes what it does (line-by-line code analysis for architectural context before vulnerability/bug finding) but has no explicit 'Use when...' clause or trigger guidance, which per the rubric caps completeness at 2, and even the 'what' is somewhat vague, placing this at 1.

1 / 3

Trigger Term Quality

Includes some relevant terms like 'code analysis', 'vulnerability', 'bug finding', and 'architectural context', but misses common user-facing variations like 'security audit', 'code review', 'static analysis', 'CVE', 'exploit', or 'debug'.

2 / 3

Distinctiveness Conflict Risk

The combination of 'ultra-granular line-by-line analysis' with 'vulnerability or bug finding' provides some distinctiveness, but it could easily overlap with general code review, security scanning, or debugging skills.

2 / 3

Total

7

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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