BD neo4j_integration
Connect to Neo4j graph databases and execute Cypher queries for storing, querying, and managing knowledge graph data using the property graph model. Full support for transactions, indexes, bulk operations, and result mapping.
Connect to Neo4j graph databases and execute Cypher queries for storing, querying, and managing knowledge graph data using the property graph model.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, consistency
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-long-hermesdescription is 225 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "title"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 40Consistency. Frontmatter name (neo4j_integration) differs from the folder (neo4j-integration)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 74 steps, 2 vague phrases
- 100Execution cost. Instruction body is 2114 tokens
- low 14 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- -31 of 1 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 225: enough signal without eating the budget
- +4Structure: 53 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (26 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.