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BF broker-weekly-monitor

Generate a weekly monitoring report for US retail brokerage stocks (IBKR, SCHW, HOOD, FUTU) AND the broader trading ecosystem including US equity/options market-wide volume (Cboe, OCC), crypto market (market cap, volume, exchange market share from The Block/CCData), and prediction markets (Polymarket/Kalshi volume from Dune Analytics). Use this skill whenever the user asks to update, generate, or review a broker monitoring report, weekly trading ecosystem update, or mentions tracking DARTs, client assets, trading volumes, margin loans, EPS revisions, US equity volume, options volume, 0DTE, put/call ratio, crypto exchange market share, prediction market volume, Polymarket, Kalshi, Dune Analytics, or The Block data. Also trigger for '券商监控', '周度监控', '零售券商', '全市场交易生态', 'weekly monitor', 'equity volume', 'options volume'.

ClawHub Agent Skills author: sarahwang94712 v1.0.0 MIT-0 6 files body ≈ 3 237 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 42/100 · Will not run — References files that are not bundled: references/report-template.md, references/excel-structure.md, references/metrics-by-broker.md

GeneratorExcelData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: references/report-template.md, references/excel-structure.md, references/metrics-by-broker.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/report-template.md
  • warning missing-ref reference to a missing file: references/excel-structure.md
  • warning missing-ref reference to a missing file: references/metrics-by-broker.md
  • warning missing-ref reference to a missing file: references/dashboard-schema.md

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: references/report-template.md, references/excel-structure.md, references/metrics-by-broker.md
  • 0Tools and files. 4 referenced file(s) missing: references/report-template.md, references/excel-structure.md, references/metrics-by-broker.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (broker-weekly-monitor) differs from the folder (broker-monitor)
  • 55Failures and branches. 1 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 94 steps
  • 100Execution cost. Instruction body is 3237 tokens
  • 100Running it twice. Mutating operations check current state

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 828: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 94 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill is a disclosed financial-reporting workflow that gathers public market data and writes report/workbook outputs, with no evidence of hidden credential access, exfiltration, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026