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autonomous-agent-patterns

Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.

57

Quality

66%

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

Quality

Content

50%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 body is a well-organized catalog of concrete, mostly executable pattern code, but it functions as an inlined code library rather than a skill: it spends most of its tokens on generic Python Claude could write itself, ships no reference files to split the bulk, and provides no sequenced workflow or validation checkpoints. Actionability is its strongest dimension; conciseness is its weakest.

Suggestions

Cut the generic, boilerplate classes (AgentLoop, Tool base class, CODING_AGENT_TOOLS dict) down to the non-obvious deltas — the genuinely novel patterns like the edit tool's occurrence-count validation and the approval manager's session caching — and trust Claude to write the scaffolding.

Move the browser automation, MCP integration, and context/checkpoint sections into references/ files (e.g. references/browser.md, references/mcp.md), keeping SKILL.md as a concise overview with one-level-deep, clearly signaled links.

Add a short sequenced workflow for assembling an agent (architecture → tools → permissions → sandbox → verify) with explicit validation checkpoints, and turn the unanchored Best Practices checklist items into verifiable steps.

DimensionReasoningScore

Conciseness

The body is ~700 lines of generic Python (agent loop, tool schema, sandbox, checkpoint, MCP classes) that an intelligent model could write unaided — the skill restates patterns Claude already knows rather than adding non-obvious knowledge. Padded sections include the descriptive CODING_AGENT_TOOLS dict and near-boilerplate class scaffolding. Not a 1 because there is little concept-explaining prose; not a 3 because the volume of redundant code is substantial rather than incidental.

2 / 5

Actionability

Most examples are concrete, near-executable code with real details — the edit tool validates occurrence counts before replacing, the sandbox validates paths and command allowlists, the approval manager caches per-session approvals. Not a 5 because examples depend on undefined imports/classes (ToolResult, playwright, base64, Any, `from mcp import Server`) and no runnable entry point ties them together; not a 3 because the guidance is well beyond pseudocode.

4 / 5

Workflow Clarity

Numbered sections give an implicit order (architecture → tools → permissions → browser → context → MCP) and checklists exist, but there is no sequenced process for applying these patterns and no validation checkpoints or feedback loops — the checklists are unanchored "[ ]" items with no verification steps. Matches the 3 anchor (sequence present but checkpoints missing); a 4 would require most checkpoints being present.

3 / 5

Progressive Disclosure

The body has clear section headers, but there are no bundle files at all — the entire pattern library (700+ lines) is inlined in SKILL.md, and content like the full browser-automation or MCP code clearly belongs in separate reference files. Matches the 3 anchor (some structure, but content that should be separate is inline). Not a 2 because headers and a resources section give reasonable navigation; not a 4 because nothing is split out despite clear candidates.

3 / 5

Total

12

/

20

Passed

Description

83%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 description that explicitly states both what the skill covers and when to use it, with four concrete capability areas and natural trigger phrases. Main weaknesses are minor: it lists coverage topics rather than concrete actions, and it misses a few common synonyms (tool calling, agent loop, MCP).

DimensionReasoningScore

Specificity

"Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows" lists several specific coverage areas. Not a 5 because this is a topic inventory ("Covers X") rather than multiple concrete actions like "extract text, fill forms, merge documents"; not a 3 because it names four distinct concrete sub-areas, not just 1-2.

4 / 5

Completeness

Both parts are explicit: the "what" ("Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows") and the "when" ("Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants") with concrete trigger phrases. Matches the 5 anchor exactly.

5 / 5

Trigger Term Quality

"Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants" provides natural phrases a user would say. Not a 5 because common variations like "tool calling", "agent loop", "MCP", or "browser automation" (which appears only in the what-clause) are missing; not a 3 because coverage goes beyond a couple of generic keywords.

4 / 5

Distinctiveness Conflict Risk

The design-patterns-for-autonomous-coding-agents framing is a fairly clear niche, but "building AI agents" and "implementing permission systems" are broad enough to overlap with general agent-building, tool-use, or MCP skills. Not a 5 (minor overlap risk remains); not a 3 (the niche is more distinct than "Works with document files").

4 / 5

Total

17

/

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

skill_md_line_count

SKILL.md is long (762 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
davila7/claude-code-templates
Reviewed

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