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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.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./backend/cli/skills/llm-tools/autogpt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 dense, actionable reference for the AutoGPT platform with strong code examples and clearly sequenced workflows supported by troubleshooting feedback loops. Its weaknesses are length and duplication: Forge, benchmarking, deployment, and troubleshooting content is inlined in SKILL.md while also existing in the reference files, which both hurts conciseness and slightly muddies progressive disclosure.

Suggestions

Move the Forge development, benchmarking, and deployment sections into references/advanced-usage.md and leave a one-line pointer in SKILL.md to reduce duplication and improve conciseness.

Collapse the inline 'Common issues' section into a pointer to references/troubleshooting.md, keeping only the single most frequent gotcha inline.

Add an explicit validation checkpoint to the Quick start workflow (e.g. 'Verify services: docker compose ps' before starting the frontend) to strengthen workflow clarity.

DimensionReasoningScore

Conciseness

The body is mostly efficient reference material (tables and code) without explaining basic concepts Claude already knows, but it is long and inlines Forge, benchmarking, deployment, and troubleshooting content that duplicates the provided references and could be tightened.

3 / 5

Actionability

Abundant concrete, copy-paste-ready commands and code (docker compose, API HTTP examples, WebSocket snippet, Forge commands, docker-compose YAML), with only minor placeholders such as perform_search(query) and ellided connection strings.

4 / 5

Workflow Clarity

Quick start, visual builder, and Forge workflows are clearly sequenced, and the monitoring and Common issues sections provide feedback loops for error recovery; the primary setup workflow lacks an inline validation checkpoint, a minor gap.

4 / 5

Progressive Disclosure

Two real one-level-deep references (advanced-usage.md, troubleshooting.md) are clearly signaled in a References section, but the body inlines deployment, custom-block, and troubleshooting material that overlaps with those references, a minor organization gap.

4 / 5

Total

15

/

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 strong: it clearly answers both what the skill does and when to use it with concrete, natural trigger phrases in third person. Its main limitation is that the listed actions are overlapping variations on agent building rather than a broad set of distinct capabilities, and there is minor overlap risk with adjacent agent frameworks.

DimensionReasoningScore

Specificity

Lists several concrete actions ('building and deploying continuous agents', 'creating visual workflow agents', 'building complex multi-step AI automation systems'), but they are variations on a single theme rather than distinct capabilities, leaving minor coverage gaps short of a 5.

4 / 5

Completeness

Explicitly states both what it does ('Autonomous AI agent platform for building and deploying continuous agents') and when to use it via a concrete 'Use when...' clause with multiple trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Good coverage of natural phrases users would say ('visual workflow agents', 'autonomous agents', 'multi-step AI automation') with some synonym variation, though a few natural terms (e.g. 'AI agents', 'agentic workflows') are absent.

4 / 5

Distinctiveness Conflict Risk

'Autonomous AI agent platform' is a clear niche with distinct triggers, but the broad agent-automation language overlaps with closely related frameworks (CrewAI/LangChain) the body itself names as alternatives, so minor conflict risk remains.

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.

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
synthetic-sciences/openscience
Reviewed

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