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ai-native-cli

Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

50

Quality

55%

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SecuritybySnyk

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tessl review fix ./skills/ai-native-cli/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

52%Scale 1-5

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

This skill is a comprehensive specification document that successfully catalogs 98 rules for agent-friendly CLI design with concrete examples and clear certification levels. However, it suffers from significant verbosity — inlining all rule details rather than using progressive disclosure, explaining concepts Claude already knows, and repeating information between sections. It would benefit greatly from being restructured as a concise overview with detailed rules split into separate reference files.

Suggestions

Split the detailed rule listings (Levels 1-3) into separate reference files (e.g., LEVEL1-CORE.md, LEVEL2-RECOMMENDED.md, LEVEL3-ECOSYSTEM.md) and keep only the implementation checklist and key examples in SKILL.md

Remove the Overview section's explanatory text and the 'When to Use This Skill' section — Claude can infer these from the content itself

Add executable code examples showing how to implement key patterns: e.g., a Python/Node error handler function that produces the required JSON error format, or a wrapper that handles --human/--agent output switching

Add a verification step to the implementation checklist, such as a compliance-checking script or a set of test commands to validate each certification level

DimensionReasoningScore

Conciseness

The skill is significantly verbose for its purpose. It extensively lists all 98 rules across three certification levels, includes explanatory text about concepts Claude already understands (what JSON is, what stderr is, what exit codes mean), and repeats information between the rules section and the implementation checklist. The overview section explains what the spec is rather than just providing it. Much of this could be condensed.

2 / 5

Actionability

The skill provides concrete, specific rules with exact flag names, exit codes, JSON schemas, directory structures, and bash examples. The implementation checklist gives clear steps. However, it lacks executable code snippets showing how to actually implement these patterns (e.g., an error handler function, a JSON output wrapper), making it more of a specification than a hands-on guide.

4 / 5

Workflow Clarity

The three-phase implementation checklist provides a clear sequence for adoption, and the certification levels create a logical progression. However, there are no explicit validation/verification steps — no guidance on how to test compliance with each level, no 'validate your implementation' checkpoints, and no feedback loops for checking whether rules are properly implemented before moving to the next phase.

4 / 5

Progressive Disclosure

With no bundle files, all 98 rules are inlined into a single massive document. The detailed rule listings for Levels 2 and 3 should clearly be in separate reference files, with the SKILL.md serving as an overview pointing to them. The reserved flags table, exit code table, and per-level rule details would benefit from being split into separate files for better navigation and token efficiency.

2 / 5

Total

12

/

20

Passed

Description

58%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 does a reasonable job of conveying what the skill covers — a comprehensive design spec for agent-friendly CLI tools — with several specific subtopics listed. Its main weakness is the absence of an explicit 'Use when...' clause, which limits completeness and makes it harder for Claude to know exactly when to select this skill. Trigger term coverage could also be improved with more natural user-facing synonyms.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when designing or reviewing CLI tools intended for AI agent consumption, or when the user asks about making command-line interfaces machine-friendly.'

Include natural synonyms and variations such as 'command line', 'terminal commands', 'shell tools', 'machine-readable output', and 'agentic tooling' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Lists several specific areas covered: structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description. These are concrete topics, though they describe what the spec covers rather than actions Claude performs with it.

4 / 5

Completeness

The 'what' is reasonably clear — it's a design spec with 98 rules for building agent-friendly CLI tools, covering specific areas. However, there is no explicit 'when' clause (e.g., 'Use when building CLI tools for agent consumption' or similar trigger guidance), which caps this at 3 per the rubric guidelines.

3 / 5

Trigger Term Quality

Includes relevant terms like 'CLI tools', 'AI agents', 'JSON output', 'error handling', 'exit codes', but misses natural user phrases like 'command line', 'terminal', 'shell commands', 'machine-readable output', or 'agentic tools'. Some terms are present but coverage of synonyms and variations is incomplete.

3 / 5

Distinctiveness Conflict Risk

The niche of 'CLI tools for AI agents' is fairly distinct and unlikely to overlap with most other skills. However, it could potentially conflict with general CLI design skills or general agent-building skills. The mention of '98 rules' and specific subtopics like 'safety guardrails' and 'agent self-description' help differentiate it.

4 / 5

Total

14

/

20

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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