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ai-agents-architect

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

47

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

50%

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

The body is a well-organized, information-dense reference of agent patterns and anti-patterns that respects Claude's competence, but it is monolithic with no external references, contains redundancy between sections, and offers descriptive guidance rather than executable, validated workflows.

Suggestions

Split the long 'Patterns' and 'Sharp Edges' sections into reference files (e.g., patterns.md, sharp-edges.md) with concise pointers from SKILL.md to improve progressive disclosure.

Add explicit validation/feedback checkpoints to the workflows (e.g., 'verify agent output before proceeding', 're-validate after replanning') to lift workflow clarity.

Remove redundancy (delete the verbatim description repeat and merge 'Capabilities' with 'Expertise') and collapse the 12 near-identical 'When to Use' triggers into a compact list.

DimensionReasoningScore

Conciseness

The body avoids explaining concepts Claude already knows and stays largely skimmable, but contains redundancy (the description text repeats verbatim, 'Capabilities' restates 'Expertise') and padded sections (12 near-identical 'User mentions or implies' bullets). It is not a 1 (no filler concept explanations) and not a 3 (redundancy and padding could be tightened).

2 / 3

Actionability

Sharp-edges 'Recommended fix' lists and pattern steps offer some concrete guidance ('5-10 tools maximum per agent', 'max_iterations on agent loops'), but there are no executable code/commands or copy-paste examples. As an instruction-only skill it is exempt from code-absence, yet the guidance remains mostly descriptive. Not a 1 (concrete bullets exist) and not a 3 (no executable, complete examples).

2 / 3

Workflow Clarity

Patterns are sequenced ('Planning phase -> Execution phase -> Replanning'; ordered checkpoint steps), but validation/feedback checkpoints are only implicit and there are no explicit verify-then-proceed steps for risky operations, which caps workflow clarity at 2. Not a 1 (sequences are present) and not a 3 (no explicit validation steps).

2 / 3

Progressive Disclosure

No bundle files exist; everything is inline in a single ~330-line SKILL.md, well-organized by headers but over the simple-skill threshold with content (patterns, sharp edges) that could be split into separate files. Not a 1 (good section organization) and not a 3 (monolithic, content that should be separate is inline, no external references).

2 / 3

Total

8

/

12

Passed

Description

50%

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 clearly states the skill's domain and lists relevant subsystems, but lacks an explicit 'Use when...' trigger clause and leans on technical terminology over natural user phrasing. It is competent but generic enough to overlap with adjacent skills.

Suggestions

Add an explicit 'Use when...' clause naming concrete user signals (e.g., 'Use when building autonomous agents, tool-using agents, or multi-agent systems').

Replace jargon-heavy phrases ('multi-agent orchestration', 'planning strategies') with natural terms users actually say ('multi-agent', 'agent planning').

List discrete concrete actions (e.g., 'design agent loops, define tool schemas, add memory and checkpointing') rather than enumerating abstract capability areas.

DimensionReasoningScore

Specificity

Names the AI-agent domain and several action areas ('designing and building autonomous AI agents', 'tool use, memory systems, planning strategies, multi-agent orchestration'), but enumerates domain areas rather than discrete concrete actions. It is not a 1 (vague/abstract) because it identifies specific subsystems, and not a 3 because it lacks a list of multiple specific concrete actions.

2 / 3

Completeness

Answers 'what' (designing/building autonomous AI agents) but has no 'Use when...' clause or explicit trigger guidance, which per the judging guidelines caps completeness at 2. Not a 1 because the 'what' is clearly stated; not a 3 because the 'when' is entirely missing.

2 / 3

Trigger Term Quality

Contains several natural terms users would say ('AI agent', 'tool use', 'multi-agent'), but leans technical ('planning strategies', 'multi-agent orchestration') and misses common variations. Not a 1 because relevant keywords are present; not a 3 because natural-term coverage is partial.

2 / 3

Distinctiveness Conflict Risk

The autonomous-agent orchestration niche is reasonably distinct but could overlap with related skills like prompt-engineer or backend. It is not a 1 (clearly more specific than generic) and not a 3 (some overlap risk with adjacent skills).

2 / 3

Total

8

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
sickn33/antigravity-awesome-skills
Reviewed

Table of Contents

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