SKILLEMALL.ai

BD substreams-websocket

Connect to and consume a substreams-websocket fan-out server — a Substreams-to-WebSocket bridge that broadcasts decoded `sf.substreams.sink.database.v1.DatabaseChanges` blocks as JSON. Use when subscribing to real-time blockchain table data (swaps, transfers, balances, etc.) over WebSocket via `<network>@<table>` selectors, applying server-side SQE event filters, or handling reconnects, chain reorgs, and slow-client backpressure for such a feed.

ClawHub Agent Skills author: Pinax v0.6.3 MIT-0 2 files body ≈ 5 014 tokens Open the sourceclawhub.ai analyzed 2 d ago

Connect to and consume a substreams-websocket fan-out server — a Substreams-to-WebSocket bridge that broadcasts decoded…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
75
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token SKILL.md:85
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "input_mint": "So11…112",
    quoted

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5014 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 44/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (substreams-websocket) differs from the folder (pinax-websockets)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5014 tokens
  • 85Steps. 46 steps, 1 vague phrases
  • 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 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (11 tags): a typed call is more reliable

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
  • +2Single-language instructions
  • +3Description length 449: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (15 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a documentation-only skill for consuming a blockchain WebSocket feed, with no executable code or hidden high-risk behavior found.
LLM: benign (high) · VirusTotal: · 20 Jun 2026