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CD USStats

Query the configured long-run US almanac (90+ annual series on economy, debt, cost of living, health, crime, family, trust, energy, many back to the 1940s: trends, verdicts, movers, correlations, freshness vs source datasets), and pull 66 current indicators from FRED, EIA and Treasury into the local US-Common-Metrics dataset for a 10y/5y/2y/1y read of the economy now. USE WHEN usstats, US stats, US indicators, long-run US trends, is X getting better or worse in America, US crime trend, wage trend, inflation history, correlate US indicators, compare decades, is the usstats data fresh, how is the economy, economic overview, economic metrics, economic trends, GDP, inflation, unemployment, gas prices, mortgage rates, FRED, US metrics, refresh data, refresh the economic data, refresh US-Common-Metrics. NOT FOR pathogen surveillance, personal finances or investments, rebuilding or publishing the almanac site itself, refreshing our data sites (DataRefresh).

danielmiessler/Personal_AI_Infrastructure Agent Skills author: danielmiessler 14 files · 5 scripts body ≈ 2 674 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Query the configured long-run US almanac (90+ annual series on economy, debt, cost of living, health, crime, family, trust, energy, many back to the 1940s…

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationData and analyticstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
95
Quality 40%
79
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Exfiltration exfil-secret-in-url Tools/FetchFredSeries.ts:131
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://api.stlouisfed.org/fred/series/observations?series_id=…&api_key=…&file_type=json&observation_start=…&observation_end=…
      placeholder
    • low Exfiltration exfil-secret-in-url Tools/GenerateAnalysis.ts:137
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://api.stlouisfed.org/fred/series/observations?series_id=…&api_key=…&file_type=json&observation_start=…).split('T')[0]}&observation_end
      placeholder
    • low Exfiltration exfil-secret-in-url Tools/GenerateAnalysis.ts:237
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://api.eia.gov/v2/petroleum/pri/gnd/data/?api_key=…&frequency=…&data[0]=value&facets[product][]=EPMR&facets[duoarea][]=NUS&sort[0][column]=…&sort[0][direction]
      placeholder
    • low Exfiltration exfil-secret-in-url Tools/UpdateSubstrateMetrics.ts:164
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://api.stlouisfed.org/fred/series/observations?series_id=…&api_key=…&file_type=json&sort_order=desc&limit=1`;
      placeholder
    • low Exfiltration exfil-secret-in-url Tools/UpdateSubstrateMetrics.ts:187
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://api.eia.gov/v2/petroleum/pri/gnd/data/?api_key=…&frequency=…&data[0]=value&facets[product][]=EPMR&facets[duoarea][]=NUS&sort[0][column]=…&sort[0][direction]
      placeholder

    Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "evals"

    Process rating: all ten parameters 47/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2674 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (5 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
    • +3Description length 964: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.