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BC daily-market-report

Generate daily US stock market analysis reports for user holdings, including portfolio P&L, 52-week range, analyst ratings, and actionable suggestions. Data sourced from Yahoo Finance (yfinance, no API key required).

ClawHub Agent Skills author: heiheiheibj v1.0.0 MIT-0 4 files body ≈ 779 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Generate daily US stock market analysis reports for user holdings, including portfolio P&L, 52-week range, analyst ratings, and actionable suggestions.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

AnalyzerData and analyticstype 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
78/100
safety, quality, tests
Safety 60%
84
Quality 40%
69
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Secrets in code secret-labelled-token scripts/fetch_data.py:4
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    API_KEY = 'cra7…ncg'
  • medium Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:47
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -LsSf https://astral.sh/uv/install.sh | sh
  • medium Dangerous commands cmd-execpolicy-bypass SKILL.md:52
    Runs PowerShell with execution policy bypassed
    powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  • low Secrets in code secret-password-literal scripts/fetch_data.py:4
    Hard-coded password / key literal (may be an example)
    API_KEY = 'cra7…ncg'

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 56/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 779 tokens

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
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 216: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 6 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill is mostly a stock-reporting tool, but it includes an undisclosed Finnhub script with a hardcoded API key and a runtime package install fallback.
LLM: suspicious (high) · 28 May 2026