dimensional-analysis

dimensional-analysis is a skill for Codex from OutlineDriven/outline-driven-development. It costs 38 tokens per session (1,920 once invoked), scanned A, original, Apache-2.0.

A review workflow for checking that units, precisions, scaling factors, rates, prices, shares, and conversions are used consistently in code.

In plain words
What is it for?
Use it to annotate source files, define the project's units, and report confirmed or disproved mismatches.
Why use it?
It can reveal calculations that mix incompatible measurements, especially in financial, scientific, and blockchain systems.

Skill for Codex

Written for Codex: agents/openai.yaml present.

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.

agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/dimensional-analysis
Any agent
npx skills add OutlineDriven/outline-driven-development --skill dimensional-analysis
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: 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 dimensional-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/dimensional-analysis.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/dimensional-analysis)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/dimensional-analysis"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/dimensional-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,920 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00038 $0.01920
Opus 5 $0.00019 $0.00960
Sonnet 5 $0.00008 $0.00384
Haiku 4.5 $0.00004 $0.00192

Measured today against content hash fab83495e95f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

dimensional-analysis 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 today.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.devin/skills/dimensional-analysis/SKILL.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dimensional analysis

Contract

Field Bound contract
Trigger A financial, scientific, DeFi, blockchain, or off-chain codebase contains mixed units, fixed-point precisions, scaling factors, rates, prices, shares, or conversions and needs full annotation plus validation.
Authority Reversible local: writes only comment-only dimensional annotations in in-scope source files plus DIMENSIONAL_SCOPE.json, DIMENSIONAL_UNITS.md, and a findings report in the project root; rollback is version control (revert comments) or undo (delete the three generated artifacts). No remote mutation.
Side effect Comment-only annotations in all in-scope source files; DIMENSIONAL_SCOPE.json, DIMENSIONAL_UNITS.md, and a final findings/coverage report in the project root. No executable code, types, or logic are changed.
Done Every in-scope file has terminal annotation, propagation, and validation status; no PENDING entries remain; blocked files reconcile exactly; only comments changed; confirmed and refuted mismatches are separated.

Inputs

  • Project root path (required).
  • Optional pre-existing DIMENSIONAL_UNITS.md and DIMENSIONAL_SCOPE.json for reuse, only when their project_root matches this repo and they contain the required structure.
  • No mode argument is honored; the full four-phase pipeline always runs end to end.

Procedure

  1. Bound scope. Confirm the project root. Identify every file containing numeric arithmetic with mixed units, precisions, scaling factors, rates, prices, shares, or conversions, and prioritize each as CRITICAL, HIGH, MEDIUM, or LOW. Write DIMENSIONAL_SCOPE.json to the project root with project_root, in_scope_files (all priorities), discoverer_focus_files (narrowed to CRITICAL/HIGH only when more than 50 arithmetic files are found), recommended_discovery_order, and every in-scope file initialized to step2: "PENDING", step3: "PENDING", step4: "PENDING". If no arithmetic files exist, write an empty manifest and skip to Output with zero findings. Done when: DIMENSIONAL_SCOPE.json is written with every in-scope file initialized to PENDING, or an empty manifest is written with zero findings.

Read the full file on GitHub · 46 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. today Changed · -30 tokens per session fab83495e95f
  2. 2d ago First seen · 46 lines · 68 tokens per session scan A ba5b676956b8

Subscribe to this mod's changes

dimensional-analysis is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed today), licensed Apache-2.0. It adds 38 tokens to every session and 1,920 once invoked, about $0.0002 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 2026-09-03.

Related

Other skills, from other repositories

monte-carlo

Use when the user wants Monte Carlo simulation of a PlanExe model — sampling from bounds to produce output distributions (mean/std/percentiles), threshold pass probabilities, and Pearson-correlation sensitivity rankings — given an extract-parameters-from-full JSON, a generate-bounds JSON, a generate-calculations…

PlanExeOrg/PlanExe · 71 tokens

cointegration-analysis

Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis.

agiprolabs/claude-trading-skills · 23 tokens

quant-experiment-runtime

Quant research experiment executor: discover an offline source database under the workdir's code-repo, build a panel, run a Research Artifact's entry point to compute research-object values, and evaluate IC/ICIR/RANKIC/coverage metrics. Runtime = Experiment Executor; it runs a Research Artifact via a Python-native…

CamusGIT/EvoQuant · 179 tokens

fin-paper-figure

Generate academic-quality figures (>=300 DPI) for economics and finance papers.

csmar432/finai-research · 14 tokens

fin-paper-writing

经济金融论文写作编排器。根据PAPEROUTLINE.md和REFINEDDESIGN.md,编排调用fin-paper-draft(正文写作)、fin-paper-figure(图表生成)、fin-review-loop(review循环),管理版本并确保章节间的一致性。.

csmar432/finai-research · 65 tokens

fin-brief-generator

根据用户输入或已有研究输出(文献综述/想法报告/新颖性报告),自动生成或更新FINBRIEF.md,减少用户填写负担。.

csmar432/finai-research · 42 tokens