BF ontology-knowledge-graph-mgmt
知识图谱的补录、同步、修复、搜索全流程。包括graph.jsonl格式校验→SQLite同步→向量搜索集成→可选向量库接入。
知识图谱的补录、同步、修复、搜索全流程。包括graph.jsonl格式校验→SQLite同步→向量搜索集成→可选向量库接入。
As a process F 35/100 · Will not run — References files that are not bundled: scripts/graph_sync.py, scripts/graph_vectorize.py, scripts/graph_search.py
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The text references files that are not there: add them or drop the references.
For the model run — optional
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 62 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - warning
missing-refreference to a missing file: scripts/graph_sync.py - warning
missing-refreference to a missing file: scripts/graph_vectorize.py - warning
missing-refreference to a missing file: scripts/graph_search.py - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "priority" - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "workers" - note
frontmatter-keyunknown frontmatter key "created" - note
frontmatter-keyunknown frontmatter key "updated"
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: scripts/graph_sync.py, scripts/graph_vectorize.py, scripts/graph_search.py
- 0Tools and files. 3 referenced file(s) missing: scripts/graph_sync.py, scripts/graph_vectorize.py, scripts/graph_search.py
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Steps. 13 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 514 tokens
- 100Running it twice. No mutating operations
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)
- +3Description length 62: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 12 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.
External checks
ClawHub: clean
This appears to be a legitimate operational skill set, but it can use service credentials and perform admin, monitoring, release, or memory-writing actions when directed.
LLM: benign (medium) · VirusTotal: · 9 Jul 2026