CtrlK
BlogDocsLog inGet started
Tessl Logo

autonomous-agents

You are an agent architect who has learned the hard lessons of autonomous AI. You've seen the gap between impressive demos and production disasters. You know that a 95% success rate per step means only 60% by step 10.

20

Quality

7%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/autonomous-agents/SKILL.md

The canonical home for this skill is autonomous-agents in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

14%Scale 1-3

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

This skill is essentially a skeleton or template that was never filled in with actual content. It names important concepts (ReAct, Plan-Execute, Reflection patterns) and anti-patterns but provides no actionable guidance, no code examples, no concrete workflows, and contains obvious placeholder text in the sharp edges table. The skill would need substantial work to be useful.

Suggestions

Add concrete, executable code examples for each pattern (ReAct loop, Plan-Execute, Reflection) showing actual implementation with specific tools or frameworks.

Replace the placeholder 'Issue' entries in the Sharp Edges table with real issues (e.g., 'Runaway token costs', 'Hallucinated tool calls', 'Context window overflow') and provide actual solution descriptions instead of bare headers.

Add a clear multi-step workflow for building an agent, with explicit validation checkpoints (e.g., 'Test single-step reliability before adding autonomy', 'Verify guardrails catch failure modes').

Either add detailed content for each pattern section or create separate reference files (e.g., REACT_PATTERN.md, PLAN_EXECUTE.md) with proper links for progressive disclosure.

DimensionReasoningScore

Conciseness

The opening paragraphs contain some philosophical framing that Claude already understands ('95% success rate per step means only 60% by step 10'). The capabilities list is essentially tags with no added value. However, the content is relatively short overall, so it's not egregiously verbose—just not efficiently using its tokens.

2 / 3

Actionability

The skill provides no concrete code, commands, or executable guidance. Patterns like ReAct, Plan-Execute, and Reflection are named but only given one-line descriptions with no implementation details, examples, or copy-paste ready code. The sharp edges table has placeholder 'Issue' text with solutions that are just section headers with no actual content.

1 / 3

Workflow Clarity

There are no sequenced steps, no validation checkpoints, and no feedback loops. The patterns section names multi-step workflows (ReAct, Plan-Execute, Reflection) but provides zero detail on how to actually execute them. The sharp edges table appears to be a template with placeholder content ('Issue' repeated for every row).

1 / 3

Progressive Disclosure

The content is a flat list of headings with minimal substance under each. There are no references to deeper documentation files, no links to examples or detailed guides. The 'Related Skills' section mentions other skills but provides no navigation. The structure gives the appearance of organization but each section is essentially empty.

1 / 3

Total

5

/

12

Passed

Description

0%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.

This description reads as a persona or character introduction rather than a functional skill description. It contains no concrete actions, no trigger terms, and no guidance on when to use the skill. It would be essentially unusable for skill selection among a set of available skills.

Suggestions

Replace the persona narrative with concrete actions the skill performs, e.g., 'Designs multi-step AI agent architectures, identifies failure modes in agent pipelines, and calculates compound reliability across sequential steps.'

Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about building AI agents, designing agentic workflows, evaluating agent reliability, or debugging multi-step autonomous systems.'

Remove first/second person framing and subjective claims ('You are an agent architect who has learned...') and replace with third-person functional language describing what the skill does.

DimensionReasoningScore

Specificity

The description contains no concrete actions whatsoever. It uses abstract, narrative language ('learned the hard lessons', 'seen the gap') without specifying any capabilities like designing agents, debugging pipelines, or evaluating reliability.

1 / 3

Completeness

Neither 'what does this do' nor 'when should Claude use it' is answered. There is no 'Use when...' clause or equivalent trigger guidance, and the description reads as a persona statement rather than a functional skill description.

1 / 3

Trigger Term Quality

There are no natural user-facing keywords. Terms like 'agent architect', 'autonomous AI', and 'production disasters' are vague and unlikely to match what a user would naturally say when needing help with a specific task.

1 / 3

Distinctiveness Conflict Risk

The description is extremely generic and could overlap with any AI-related skill. 'Agent architect' and 'autonomous AI' are broad enough to conflict with numerous other skills without providing a clear niche.

1 / 3

Total

4

/

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

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.