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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.

Quality

71%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/ai-native-cli/SKILL.md

The canonical home for this skill is ai-native-cli in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

A well-structured, information-dense spec body with concrete examples, tables, and a phased implementation checklist. Main weaknesses are redundant restatement of the same rules across four sections, and a monolithic single-file layout that inlines the full rule catalog instead of splitting it into reference files.

Suggestions

Consolidate the Overview, Best Practices, and Common Pitfalls sections -- they restate rules already listed under Certification Requirements and the Quick Implementation Checklist.

Move the per-level rule catalogs (Level 1/2/3) into reference files such as references/core-rules.md, references/recommended-rules.md, and references/ecosystem-rules.md, keeping SKILL.md as a concise overview with clearly signaled links.

Expand compressed rule-ID groupings (e.g., 'D2/D5/D6/D8/D10') or point to a reference file that defines each rule, since the current shorthand leaves many of the 98 rules undefined.

Add explicit per-phase validation steps to the implementation checklist (e.g., 'verify: echo output | jq .' after Phase 1) to close the workflow checkpoint gap.

DimensionReasoningScore

Conciseness

The rule catalog itself is dense and token-efficient (grouped IDs like '[P2] D2/D5/D6/D8/D10: per-command help, enums, defaults'), but the Overview, Quick Implementation Checklist, Best Practices, and Common Pitfalls sections substantially restate the same rules, adding noticeable redundancy. Not a 2 because the core content is information-dense rather than padded explanation of concepts Claude already knows.

3 / 5

Actionability

Provides concrete, executable guidance: exact error JSON shape ('{"error":true, "code":"...", "message":"...", "suggestion":"..."}'), an exit-code table, a reserved-flags table, the agent/ directory layout, and bash/JSON examples. Below 5 because compressed rule-ID groupings (e.g., 'D2/D5/D6/D8/D10') never state what each individual rule requires, leaving gaps for implementation.

4 / 5

Workflow Clarity

The Quick Implementation Checklist gives a clear Phase 1->2->3 sequence, each phase explicitly mapped to a certification level ('each phase gets you the next certification level'), which functions as a checkpoint. Below 5 because per-phase validation steps are implicit rather than explicit (e.g., no 'verify JSON passes jq .' smoke test wired into the checklist), and the 'How It Works' steps are design aspects rather than an execution sequence.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent), so the entire ~200-line 98-rule catalog is inlined in a single SKILL.md where per-level reference files (core.md, recommended.md, ecosystem.md) would be the appropriate split. Good section headers provide some structure, matching anchor 3 ('some structure but content that should be separate is inline').

3 / 5

Total

14

/

20

Passed

Description

66%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, specific description that clearly communicates what the skill covers, weakened only by the absence of any explicit 'use when' trigger guidance. Trigger terms are good but lack common synonyms like 'command line' or 'agent-friendly'.

Suggestions

Add an explicit trigger clause, e.g. 'Use when building or modifying CLI tools that AI agents will invoke, or when auditing a CLI for agent safety.'

Include natural synonyms such as 'command-line tools', 'agent-friendly', or 'automation pipelines' to broaden trigger term coverage.

State the actionable framing ('Apply these rules when designing...') rather than only describing what the spec covers.

DimensionReasoningScore

Specificity

Names the domain ('CLI tools that AI agents can safely use') and lists six concrete coverage areas ('structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description'). Falls short of 5 because these are topic labels rather than concrete actions, and stays above 3 because coverage goes well beyond 1-2 items.

4 / 5

Completeness

Has a clear 'what' (a 98-rule design spec for agent-safe CLI tools) but no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric guidelines. Not a 2 because the 'what' is specific and well-detailed.

3 / 5

Trigger Term Quality

Good keyword coverage with 'CLI tools', 'AI agents', 'structured JSON output', 'error handling', and 'exit codes' -- terms a user building an agent-facing CLI would naturally use. Missing a few natural synonyms such as 'command line' or 'agent-friendly', so not a 5.

4 / 5

Distinctiveness Conflict Risk

The niche -- CLI tools designed for safe AI-agent use -- is clearly distinguishable with distinct triggers (structured JSON output, agent self-description, safety guardrails). Minor overlap risk with general CLI design/best-practices skills keeps it below 5.

4 / 5

Total

15

/

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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills/skills/ai-native-cli/SKILL.md

Reviewed

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