autogpt-agents

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

Quality

72%

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Securityby

Low

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tessl review fix ./skills/agents/autogpt/SKILL.md

Quality

Content

61%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 thorough, mostly actionable reference with good navigation to two real bundled references. Its main weaknesses are conceptual padding that hurts conciseness and the absence of explicit validation checkpoints in destructive/batch workflows.

Suggestions

Trim conceptual exposition Claude already knows (Architecture overview, 'Blocks are reusable functional components', the graphs/nodes ASCII diagrams) to improve conciseness.

Add explicit validation checkpoints to destructive/batch workflows (e.g., verify migrations succeeded before proceeding, confirm health checks after docker compose up, validate graph before publishing).

Move deployment YAML, environment-variable tables, integrations, and benchmarking detail into the existing references to keep SKILL.md a lean overview.

Dimension	Reasoning	Score
Conciseness	The ~400-line body is mostly efficient but includes explanatory padding Claude does not need ('Blocks are reusable functional components', the Architecture overview, conceptual graphs/nodes diagrams) and could be tightened.	3 / 5
Actionability	Provides concrete executable guidance throughout (docker compose, ./run commands, REST/WebSocket examples, python blocks), with only minor illustrative gaps such as the perform_search() stub and partial credential-injection example.	4 / 5
Workflow Clarity	Multi-step sequences are present, but deployment, migrations, and clearing stuck executions are destructive/batch operations lacking explicit validate-then-proceed checkpoints, which caps workflow clarity at 3 per the rubric.	3 / 5
Progressive Disclosure	Clear section structure with two well-signaled, real one-level-deep references (advanced-usage.md, troubleshooting.md), though substantial material that could live in those files (deployment YAML, env tables, integrations, benchmarking) is inlined.	4 / 5
	Total	14 / 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.

The description is well-constructed: it states concrete capabilities and pairs them with an explicit, multi-trigger 'Use when' clause. Trigger terms are natural and the niche is distinct, with only minor gaps in synonym coverage and specificity.

Dimension	Reasoning	Score
Specificity	Names the domain and several concrete actions ('building and deploying continuous agents', 'visual workflow agents', 'persistent autonomous agents', 'multi-step AI automation systems'), with minor overlap/gaps rather than comprehensive coverage.	4 / 5
Completeness	Explicitly states both the 'what' ('platform for building and deploying continuous agents') and the 'when' via a concrete 'Use when...' clause with multiple trigger phrases.	5 / 5
Trigger Term Quality	Includes natural phrases users would say ('visual workflow agents', 'persistent autonomous agents', 'multi-step AI automation systems') with good coverage, though some synonyms and the product name itself are absent.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (continuous/autonomous agents with a visual workflow builder) with mostly distinct triggers and only minor overlap risk with adjacent orchestration skills.	4 / 5
	Total	17 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: OpenLAIR/dr-claw
Path: skills/agents/autogpt/SKILL.md
Commit: 4b35756

Reviewed: 5 days ago

Table of Contents

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