goodharts-law

goodharts-law is a skill for Claude Code, Codex from The-Artificer-of-Ciphers-LLC/skills-from-the-artificer. It costs 102 tokens per session (745 once invoked), scanned A, original, MIT.

A guide to Goodhart's Law: when a measurement becomes a target, people may optimize the number instead of the real goal. It explains this problem with examples such as code output, bug counts, test coverage, and pull requests.

In plain words
What is it for?
Use it when designing engineering metrics, goals, key performance indicators, or performance reviews, and when checking whether a number reflects the outcome you actually care about.
Why use it?
It helps avoid metrics that encourage misleading or harmful behavior. A team can spot when people are gaming a measure rather than improving the result it was meant to represent.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when designing engineering metrics, goals, key performance indicators, or performance reviews, and when checking whether a number reflects the outcome you actually care about.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/goodharts-law
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add The-Artificer-of-Ciphers-LLC/skills-from-the-artificer --skill goodharts-law
Clone the repo
git clone --depth 1 https://github.com/The-Artificer-of-Ciphers-LLC/skills-from-the-artificer

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for goodharts-law

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/goodharts-law"><img src="https://agentmods.dev/badge/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/goodharts-law.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 745 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00102 $0.00745
Opus 5 $0.00051 $0.00373
Sonnet 5 $0.00020 $0.00149
Haiku 4.5 $0.00010 $0.00075

Measured 12d ago against content hash 28aba339bd98, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

goodharts-law scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

goodharts-law/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Goodhart's Law

"When a measure becomes a target, it ceases to be a good measure." — Charles Goodhart, 1975 (popularized by Marilyn Strathern)

The core idea

The moment you tell people they'll be evaluated by a number, they start optimizing for that number — often in ways that are disconnected from, or actively harmful to, the underlying goal the number was meant to represent.

This isn't because people are bad. It's because optimizing for a proxy is easier and more legible than optimizing for the underlying reality.

Classic examples in software

What you measure What gets gamed
Lines of code written Verbose, redundant code
Bugs closed Bugs closed without fixing, or marked as duplicates
Velocity (story points) Points inflated per story
Test coverage % Trivial tests that don't assert anything meaningful
PR count Many tiny, low-value PRs
Support tickets resolved Quick closes without real resolution
Time to first response Auto-responses that count as "responses"

Why it happens

A measurement is a proxy for the thing you actually care about. When you turn the proxy into the goal, you create pressure to optimize the proxy — and the path of least resistance is often to do that without actually improving the underlying thing.

A good engineering team and a mediocre one can produce the same velocity number. A resolved ticket doesn't mean a happy customer. The number gets decoupled from reality.

How to defend against it

Use multiple metrics together, not any one metric in isolation. Gaming one metric is easy. Gaming five simultaneously, when they pull in different directions, is much harder. Pair velocity with defect rates. Pair ticket resolution with customer satisfaction.

Audit the proxy-to-reality relationship regularly. Ask: does this metric still represent what we want? Talk to people. Watch their behavior. A metric that's being gamed will show up as suspicious patterns.

Weight outcomes over outputs. Outputs (PRs merged, tickets closed) are easy to count. Outcomes (users retained, errors reduced, feature adoption) are harder to fake. Wherever possible, measure outcomes.

Read the full file on GitHub · 59 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 59 lines · 102 tokens per session scan A 28aba339bd98

Subscribe to this mod's changes

goodharts-law is a skill published in the GitHub repository The-Artificer-of-Ciphers-LLC/skills-from-the-artificer (4 stars, last pushed 10d ago), licensed MIT. It adds 102 tokens to every session and 745 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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