SKILLEMALL.ai

BB toolbelt

Toolbelt is a collaborative substrate over your data. Upload any document — entities and relationships extracted automatically, queryable immediately. Ask questions that span structured tables, documents, and relationships in a single call. No stitching databases together. Toolbelt orchestrates semantic, structured, and hybrid retrieval through one MCP server — vector, knowledge graph, SQL, geospatial, streaming. Share the URL and any agent can query the same workspace — like a shared Google Doc for your data. Built by Kinetica. Use this skill at the start of any task where an agent needs to ingest documents and have entities/relationships auto-extracted, query structured + unstructured data together in natural language, or share findings with other agents across sessions. The skill handles first-time setup: provisions a free Toolbelt account if none exists, configures the MCP connection in the agent's client, and hands off to Toolbelt's MCP tools for the actual work. NOT for one-off lookups that don't benefit from automatic extraction, hybrid retrieval, or shared state — use the agent's native tools for those.

ClawHub Agent Skills author: ToolbeltAI v1.1.0 MIT-0 2 files body ≈ 4 008 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions

ProcedureGoogle DocsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
When it triggers w 12
50
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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

  • error description-long description is 1129 chars, limit 1024

Process rating: all ten parameters 68/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 4008 tokens
  • 100Steps. 31 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • +3Description length 1128: 120–800 characters recommended
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 31 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This skill is a disclosed Toolbelt setup and data-query integration that asks for consent before network calls, config writes, uploads, sharing, or persistence-sensitive actions.
LLM: benign (high) · VirusTotal: · 10 Aug 2026