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noisefloor — is this number real?

PYPI · NOISEFLOOR · SCANNED AUG 3

Is this number real, or is it noise? Peek-safe A/B tests, change detection, honest forecasts.

Available components

68 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →

Supply Chain Security100
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
  • No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency45
Schema Quality & AI Usability83
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 827 tokens (~137/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
  • Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage96
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 89% of tool parameters carry a description.Partial
Capabilities60
  • Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

pypi · noisefloor

# add to Claude Code
claude mcp add beepboop2025-noisefloor -- uvx noisefloor
# add to Codex CLI
codex mcp add beepboop2025-noisefloor -- uvx noisefloor
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "beepboop2025-noisefloor": {
      "type": "local",
      "command": [
        "uvx",
        "noisefloor"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add beepboop2025-noisefloor --command uvx --arg noisefloor
# ~/.hermes/config.yaml
mcp_servers:
  beepboop2025-noisefloor:
    command: "uvx"
    args: ["noisefloor"]
// mcp.json
{
  "mcpServers": {
    "beepboop2025-noisefloor": {
      "command": "uvx",
      "args": [
        "noisefloor"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 2 Aug 26 +29
    • Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
    • Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet. security
    • MCP protocol: unverified → fail functional
    • Schema quality: unverified → 100 functional
    • Tool coverage: unverified → 100 functional
    • First check of Tool coverage: 89 functional
    • First check of Schema quality: fail functional
    • First check of Schema quality: fail functional
    • First check of Schema quality: excellent functional
    • Capabilities: Protocol version not yet verified: we do not have a sandbox capture of the MCP handshake this version of the package performs yet. functional
    • Tool coverage: Tool coverage not yet verified: we do not have a sandbox capture of the tool definitions this version of the package serves yet. functional
    • Schema quality: Schema quality not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet. functional
    • Package version: 0.1.2 → 0.2.0 functional
  • 31 Jul 26 +10
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 −18
    • Malware scan: pass → unverified security
  • 29 Jul 26 0
    • Tool coverage: Tool coverage not yet verified: our sandbox run of this package did not complete, so we have no tool definitions to assess. functional
    • Schema quality: Schema quality not yet verified: our sandbox run of this package did not complete, so we have no schema to assess. functional
  • 28 Jul 26 47

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Analysed pypi/[email protected]

Provenance none

Ecosystem: pypi · Outcome: none

Install scripts 1 script
Hook Tier Command
build_backend allowlisted hatchling.build
Dependencies 0 packages

0 packages in the resolved dependency tree.

MCP tools — 6 exposed · ~581 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
ab_test ~140

Can you call a winner on an A/B test yet? Uses anytime-valid confidence sequences, so it is SAFE TO RUN AFTER EVERY OBSERVATION — peeking does not inflate the false-positive rate the way a t-test or z-test does.

NameTypeReqDescription
a_labelstring
a_successesintegeryesconversions in arm A
a_totalintegeryestotal observations in arm A
alphanumbererror budget, default 0.05
b_labelstring
b_successesintegeryesconversions in arm B
b_totalintegeryestotal observations in arm B

No output schema declared.

No examples provided.

did_it_change ~103

Did a metric actually change, or is the move noise? Detects both rises AND collapses against the metric's own history, with a stated false-alarm rate and no assumption about the distribution.

NameTypeReqDescription
half_lifenumberoptional: readings after which old history counts half, for drifting metrics
two_sidedbooleandetect drops as well as rises (default true)
valuesarrayyesthe metric's history, oldest first

No output schema declared.

No examples provided.

forecast_next ~67

What should the next reading be, and within what range? Range adapts to the metric's recent volatility and stays valid even when the metric shifts.

NameTypeReqDescription
nominalnumberrange coverage, default 0.8
valuesarrayyesthe metric's history, oldest first

No output schema declared.

No examples provided.

real_or_sampling ~93

Did the metric move, or did the sample size underneath it move? Run this before reporting any RATE as a change — conversion rates, error rates and click-through all shift when the denominator shifts, for reasons that have nothing to do with the thing being measured.

NameTypeReqDescription
sample_sizesarrayyesthe denominator behind each reading, same order and length
valuesarrayyesthe metric's history, oldest first

No output schema declared.

No examples provided.

score_forecasts ~76

How good would these forecasts actually have been? Grades every prediction the tool would have made over the history, using only what was known at the time, and reports calibration plus the worst misses.

NameTypeReqDescription
nominalnumberrange coverage, default 0.8
valuesarrayyesthe metric's history, oldest first

No output schema declared.

No examples provided.

which_metrics_matter ~102

You watch many metrics; which genuinely stand out? Controls the false discovery rate across all of them at once, which per-metric thresholds do not: forty metrics each alerting wrongly 5% of the time means two false alarms every round.

NameTypeReqDescription
alphanumberfalse-discovery rate, default 0.1
evidenceobjectyesmetric name -> evidence value, e.g. the 'evidence' field from did_it_change

No output schema declared.

No examples provided.