SKILLEMALL.ai

BF stocki-financial-reader

Institutional-grade financial data skill for OpenClaw. Real-time quotes, financials, valuation time series, OHLCV history, industry membership, consensus forecasts, composite analysis. Covers cn/hk/us markets and stock/index/etf/futures/crypto. For structured market/financial data, use this skill.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Eval11 v0.4.0 MIT-0 18 files body ≈ 2 278 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 57/100 · Will not run — References files that are not bundled: references/<n>.md

AnalyzerData and analyticsInfrastructureFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
82
Quality 40%
81
Run on models
none yet
Process rating
F
57/100
Will not run
References files that are not bundled: references/<n>.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 1

  • high Dangerous commands cmd-pipe-to-shell INSTALL.md:8
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://skillhub.cn/install/install.sh | bash

Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/<n>.md

Process rating: all ten parameters 57/100

Will not run. References files that are not bundled: references/<n>.md
  • 0Tools and files. 1 referenced file(s) missing: references/<n>.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 27 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2278 tokens
  • 100Progress reporting. Reports progress

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)
  • -2localhost URLs: will not work for another user
  • -31 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 298: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (9 of 9)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a disclosed financial-data reader that uses a Stocki API key to fetch market data and includes expected setup diagnostics.
LLM: benign (high) · VirusTotal: · 28 May 2026