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langgraph

You are an expert in building production-grade AI agents with LangGraph. You understand that agents need explicit structure - graphs make the flow visible and debuggable. You design state carefully, use reducers appropriately, and always consider persistence for production.

Quality

61%

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tessl review fix ./plugins/antigravity-bundle-agent-architect/skills/langgraph/SKILL.md

The canonical home for this skill is langgraph in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

57%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 solid patterns library with three complete, commented code examples and useful anti-pattern guidance. Weaknesses are the verbatim duplicate of the description in the Role section, a missing import that breaks one example's executability, and the absence of any validation/debugging checkpoint guidance despite debugging being flagged as a limitation.

Suggestions

Remove the Role paragraph that restates the frontmatter description verbatim, and drop filler requirements like "Understanding of graph concepts".

Fix the State-with-Reducers example to import add_messages (from langgraph.graph.message import add_messages), and fence the anti-pattern should_continue snippet as a python code block.

Add a brief verification/debugging section (e.g., printing checkpointed state or asserting exit conditions) since Limitations flags debugging as challenging but offers no guidance for it.

DimensionReasoningScore

Conciseness

Mostly efficient, code-dense content, but the opening Role paragraph duplicates the frontmatter description verbatim ("You are an expert in building production-grade AI agents with LangGraph..."), and the Requirements section includes filler Claude doesn't need ("Understanding of graph concepts"), matching anchor 3 ('mostly efficient but includes some unnecessary explanation').

3 / 5

Actionability

Three substantial, mostly executable code examples with inline comments ("# add_messages reducer appends, doesn't overwrite", numbered steps 1-7 in the basic graph), matching anchor 4. Not 5 because the State-with-Reducers example uses add_messages without importing it, and the anti-pattern should_continue snippet is unfenced plain text rather than a runnable code block.

4 / 5

Workflow Clarity

Each pattern is internally sequenced ("1. Define State" ... "7. Run") with 'When to use' notes, but there are no validation or verification checkpoints anywhere (e.g., inspecting graph output or checkpointed state), even though Limitations concedes "Debugging can be challenging" — anchor 3 ('steps listed but validation gaps').

3 / 5

Progressive Disclosure

The ~290-line body is well-sectioned (Patterns, Anti-Patterns, Limitations) but entirely monolithic with no bundle files; the three full code patterns are content that could plausibly live in one-level-deep reference files, matching anchor 3 ('some structure but... content that should be separate is inline').

3 / 5

Total

13

/

20

Passed

Description

48%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 identifies a clear niche (LangGraph agent development) but is framed as a second-person persona statement rather than a third-person capability description, and it entirely lacks a 'Use when...' trigger clause. Keyword coverage is adequate but misses common variations like 'StateGraph', 'workflow', and 'checkpointing'.

Suggestions

Rewrite in third person leading with capabilities, e.g.: "Builds production-grade AI agents with LangGraph: constructs StateGraphs, designs state with reducers, adds conditional routing, checkpointers, and human-in-the-loop patterns."

Add an explicit trigger clause, e.g.: "Use when building, extending, or debugging LangGraph agents, StateGraph workflows, or multi-agent pipelines in Python."

Include natural trigger terms users would actually say, such as "StateGraph", "agent graph", "checkpointing", and "tool-calling loop".

DimensionReasoningScore

Specificity

The description names the domain and a few actions ("building production-grade AI agents with LangGraph", "design state carefully", "use reducers appropriately", "always consider persistence"), which matches anchor 3, but it is written entirely in second person ("You are an expert", "You design state carefully"), which the guidelines penalize by reducing specificity by 1.

2 / 5

Completeness

The 'what' is reasonably clear (expert agent construction with LangGraph covering state design, reducers, and persistence), but there is no 'Use when...' clause or equivalent trigger guidance, so completeness is capped at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Relevant keywords are present ("LangGraph", "AI agents", "state", "reducers", "persistence"), but common natural phrasings users would say — "agent graph", "StateGraph", "workflow", "checkpointing", "human-in-the-loop" — are missing, matching anchor 3 ('some relevant keywords but missing common variations or synonyms').

3 / 5

Distinctiveness Conflict Risk

"LangGraph" names a specific framework, giving a clear niche with distinct triggers; only minor overlap risk exists with closely related agent-building skills (the body itself lists "crewai" as related). Not 5 because "production-grade AI agents" alone is broad and could collide with generic agent skills.

4 / 5

Total

12

/

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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/antigravity-bundle-agent-architect/skills/langgraph/SKILL.md

Reviewed

Table of Contents

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