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autonomous-agents

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

40

Quality

38%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./cli-tool/components/skills/ai-research/autonomous-agents/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

22%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.

The content is a broken, contentless skeleton: the intro is truncated mid-sentence ("logging befor"), the Anti-Patterns sections are empty headers, and the Sharp Edges table — the skill's one substantive artifact — is filled with 'Issue' placeholders and leaked markdown headers instead of real issues, severities, and solutions. There is nothing an agent could act on; the skill needs real content written into every section before structural polish matters.

Suggestions

Fill the Anti-Patterns sections with actual content: for each (Unbounded Autonomy, Trusting Agent Outputs, General-Purpose Autonomy) describe the failure mode and what to do instead, or delete the empty headers.

Rebuild the Sharp Edges table with real issue names (e.g. 'Compounding error rates across steps'), accurate severities, and plain-text solutions — currently every row reads 'Issue | critical | ## ...', which is placeholder corruption, not guidance.

Replace the persona intro and kebab-case capabilities list with concrete guidance: how to structure a ReAct/Plan-Execute loop, when to add reflection, and validation checkpoints (e.g. test at scale before production, validate outputs against ground truth) as executable workflow steps.

DimensionReasoningScore

Conciseness

The body is short and free of concept over-explanation, but it wastes tokens on persona padding ("You are an agent architect who has learned the hard lessons"), a filler kebab-case capabilities list, and empty sections. It fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than 4, because the filler and truncated intro provide no usable content at all.

3 / 5

Actionability

No concrete code, commands, or executable guidance appear anywhere. The Patterns section offers only one-line abstractions ("Alternating reasoning and action steps"), Anti-Pattern headers have zero content, and the Sharp Edges table rows are placeholder text ("Issue | critical | ## Reduce step count"). This matches the 'entirely vague or abstract; only describes rather than instructs' anchor, and there is no lower anchor.

1 / 5

Workflow Clarity

There is no sequence of steps and no validation checkpoints; the one structure that implies a workflow (the Sharp Edges table) is incoherent, with 'Issue' placeholders in every row and markdown headers ('## Reduce step count') leaking into the Solution column. This matches the 'steps missing or incoherent; no sequence; no validation' anchor.

1 / 5

Progressive Disclosure

The skill has no bundle files (no references/, scripts/, or assets/ directories) and section headers exist, so there are no nested or buried references. But the structure is nominal and hollow — empty Anti-Pattern sections and a corrupted table give no navigational value — fitting 'some structure but could be better organized' rather than 4.

3 / 5

Total

8

/

20

Passed

Description

55%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.

The description communicates a clear domain and named capabilities but reads as a marketing blurb: it spends tokens on editorial commentary ("The challenge isn't making them capable - it's making them reliable", "Key insight: compounding error rates kill autonomous agents") instead of trigger guidance, includes no 'Use when' clause, and is cut off mid-sentence. It would benefit most from an explicit trigger clause and removing the truncated statistics sentence.

Suggestions

Add an explicit trigger clause, e.g. 'Use when designing or debugging autonomous AI agents, agent loops, or agent reliability issues.'

Remove the editorial commentary ('The challenge isn't...', 'Key insight:...') and the mid-sentence truncated statistic — they consume description budget without aiding skill matching.

Add natural trigger synonyms users would actually say ('building AI agents', 'reliable agents', 'agent framework') to distinguish this skill from sibling agent skills like multi-agent-orchestration.

DimensionReasoningScore

Specificity

The description lists several named, specific coverage areas — "agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability" alongside "decompose goals, plan actions, execute tools, and self-correct" — matching the 'several specific actions; minor gaps' anchor. It is not a 5 because the actions are conceptual domains rather than comprehensive concrete operations, and the sentence is truncated mid-list ("drops to 60% b").

4 / 5

Completeness

The "what" is clear ("This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability") but there is no "Use when..." or equivalent trigger clause, which explicitly caps completeness at 3 per the judging guidelines. It cannot score 4 because the "when" is entirely missing rather than merely implicit, and the truncation further weakens the statement.

3 / 5

Trigger Term Quality

Relevant keywords exist ("autonomous agents", "agent loops", "ReAct", "Plan-Execute", "goal decomposition", "reflection patterns") but they lean technical and miss the natural phrases a user would say, such as "building agents", "AI agents", or "reliable agents". Not a 4 because common variations and synonyms are absent, not merely a few missing.

3 / 5

Distinctiveness Conflict Risk

Naming ReAct, Plan-Execute, and reflection patterns gives it some specificity, but "autonomous agents" is the umbrella term for a family of sibling skills the body itself lists (multi-agent-orchestration, agent-tool-builder, agent-memory-systems, agent-evaluation), creating real overlap risk. It is not a 4 because no trigger guidance distinguishes it from those closely related skills.

3 / 5

Total

13

/

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
davila7/claude-code-templates
Reviewed

Table of Contents

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