measurement-discipline

measurement-discipline is a skill for Claude Code from cdeust/zetetic-team-subagents. It costs 71 tokens per session (708 once invoked), scanned A, original, MIT.

A method for auditing how a metric is defined and measured before relying on it. It checks the unit, measurement procedure, inputs, outputs, and effects of observing the system.

In plain words
What is it for?
Investigating unreliable improvements, defining repeatable metrics, balancing data or time flows, and finding missing requests, money, or information.
Why use it?
It helps explain numbers that do not add up, metrics that measure the wrong thing, and measurements distorted by the act of measuring.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the zetetic-team-subagents plugin — 16 skills, 2 commands, 23 agents, 7 hooks, 1 MCP server shipped together

Good fit Investigating unreliable improvements, defining repeatable metrics, balancing data or time flows, and finding missing requests, money, or information.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cdeust/zetetic-team-subagents/measurement-discipline
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 cdeust/zetetic-team-subagents --skill measurement-discipline
Clone the repo
git clone --depth 1 https://github.com/cdeust/zetetic-team-subagents

Made for: Claude Code.

Or install zetetic-team-subagents, the plugin that ships this one along with the rest of its 16 skills, 2 commands, 23 agents, 7 hooks, 1 MCP server.

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 measurement-discipline

README.md
[![agentmods](https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/measurement-discipline/github.svg)](https://agentmods.dev/skills/cdeust/zetetic-team-subagents/measurement-discipline)
Your own site
<a href="https://agentmods.dev/skills/cdeust/zetetic-team-subagents/measurement-discipline"><img src="https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/measurement-discipline/github.svg" alt="Measured on agentmods" height="20"></a>

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.

agentmods 80×15 button for measurement-discipline

Your own site · 80×15
<a href="https://agentmods.dev/skills/cdeust/zetetic-team-subagents/measurement-discipline"><img src="https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/measurement-discipline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 708 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 $0.00071 $0.00708
Opus 5 $0.00036 $0.00354
Sonnet 5 $0.00014 $0.00142
Haiku 4.5 $0.00007 $0.00071

Measured 12d ago against content hash 8e28a53f2c6a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

measurement-discipline 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.

skills/measurement-discipline/SKILL.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Measurement Discipline

Problem shape: a quantity is being read, improved, or argued about, but the instrument, the unit, or the conservation ledger behind it has never been audited. Symptoms: residuals outside noise, metrics without operational definitions, inputs and outputs that don't balance, observer effects, one-method-only results.

Relevant geniuses

Agent Use when
curie measured > predicted from known parts; instrument missing or unit undefined; measurement may perturb the system (Heisenbugs, observability overhead)
shannon "improving X" where X has no formal definition; method proposed without knowing the theoretical limit; a metric with no repeatable procedure
lavoisier money, data, requests, or time "disappearing"; inputs and outputs never balanced; the residual needs a name and a carrier
galileo phenomenon obscured by secondary effects; too fast/large/rare to observe directly; qualitative claims that need a number
einstein a concept in the metric has no measurement procedure; the rule gives different answers from different viewpoints
deming reacting to noise as if it were signal — common vs special cause not separated
ekman a "subjective" domain needs objective coding; signal hides below normal temporal resolution; per-subject baselines missing
wu a "law" or assumption everyone trusts has never actually been tested; increased precision could refute it

Invocation

  1. Pick the best-fit agent above. If two or more fit, run tools/genius-invoker.sh route "<problem>" and take the top ranked match.
  2. Load it: tools/genius-invoker.sh invoke <agent> "<problem>", then read agents/genius/<agent>.md in full.
  3. Apply the agent's <workflow> step by step — do not skip steps — and answer in its <output-format>.
  4. Chain when the problem spans shapes (e.g. lavoisier finds the residual, curie isolates its carrier): tools/genius-invoker.sh compose lavoisier curie -- "<problem>".
  5. If no shape above matches, do not force a genius — use a standard team agent (INDEX.md routing rule).

Read the full file on GitHub · 49 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 · 49 lines · 71 tokens per session scan A 8e28a53f2c6a

Subscribe to this mod's changes

measurement-discipline is a skill published in the GitHub repository cdeust/zetetic-team-subagents (7 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 708 once invoked, about $0.0004 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.

Related

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