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trust-velocity-calculator

Helps calculate the rate at which trust in a skill or agent is decaying by combining time elapsed since last verification with the rate of change in behavior, permissions, or dependencies — producing a trust velocity score that predicts when a trusted credential will become unreliable.

andyxinweiminicloud0 source installs☆ 0 Repository starsv1.0.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install andyxinweiminicloud/trust-velocity-calculator

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View source ↗Guides

Skill instructions

Trust Doesn't Just Decay. It Decays Faster When Things Change.

Helps identify when a trusted skill or agent is losing reliability faster than time alone would suggest — by measuring both elapsed time and the rate of change in behavior, permissions, and dependencies.

Problem

A verification badge from 18 months ago represents less trust than a badge from 3 months ago. That much is intuitive. What's less intuitive is that a badge from 6 months ago on a skill that has received 8 updates in the last 4 weeks represents less trust than a badge from 12 months ago on a skill that hasn't changed at all.

Trust decay is not linear with time. It accelerates with change velocity. A skill that updates frequently is either actively maintained (good) or actively modified toward new objectives (potentially bad). The update rate is a multiplier on decay — high velocity amplifies uncertainty. A skill with a high change rate and an old audit badge is more uncertain than a skill with a low change rate and the same old badge, because more surface area has changed without re-verification.

Current trust models treat verification as binary and time-independent: verified or not, with a vague sense that older is riskier. Trust velocity makes the decay quantitative: trust score = baseline × time_factor × (1 - change_velocity_penalty).

What This Calculates

This calculator produces trust velocity assessments across five dimensions:

  1. Time decay factor — How much has raw elapsed time since last verification reduced the baseline trust score? Configurable decay curves: linear, exponential, or step-function by verification type
  2. Change velocity multiplier — How many meaningful changes (permission expansions, new endpoints, dependency updates, instruction drift) have occurred per unit time since last verification? Higher velocity = faster decay
  3. Volatility window — Is the current update rate higher or lower than the skill's historical baseline? A su...

Source information

Source
github
Repository
openclaw/skills
Path
skills/andyxinweiminicloud/trust-velocity-calculator
Version
1.0.0
Commit
434e669b92bac04680ec60f125ed9785726971a3
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Trust Doesn't Just Decay. It Decays Faster When Things Change.

> Helps identify when a trusted skill or agent is losing reliability faster than time alone would suggest — by measuring both elapsed time and the rate of change in behavior, permissions, and dependencies.

## Problem

A verification badge from 18 months ago represents less trust than a badge from 3 months ago. That much is intuitive. What's less intuitive is that a badge from 6 months ago on a skill that has received 8 updates in the last 4 weeks represents less trust than a badge from 12 months ago on a skill that hasn't changed at all.

Trust decay is not linear with time. It accelerates with change velocity. A skill that updates frequently is either actively maintained (good) or actively modified toward new objectives (potentially bad). The update rate is a multiplier on decay — high velocity amplifies uncertainty. A skill with a high change rate and an old audit badge is more uncertain than a skill with a low change rate and the same old badge, because more surface area has changed without re-verification.

Current trust models treat verification as binary and time-independent: verified or not, with a vague sense that older is riskier. Trust velocity makes the decay quantitative: trust score = baseline × time_factor × (1 - change_velocity_penalty).

## What This Calculates

This calculator produces trust velocity assessments across five dimensions:

1. **Time decay factor** — How much has raw elapsed time since last verification reduced the baseline trust score? Configurable decay curves: linear, exponential, or step-function by verification type
2. **Change velocity multiplier** — How many meaningful changes (permission expansions, new endpoints, dependency updates, instruction drift) have occurred per unit time since last verification? Higher velocity = faster decay
3. **Volatility window** — Is the current update rate higher or lower than the skill's historical baseline? A su...

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