dimensional-analysis

What this skill does

# Dimensional Analysis Skill

This skill orchestrates a dimensional-analysis pipeline for codebases that perform numeric computations with mixed units, precisions, or scaling factors. The main skill context is a workflow controller only: it delegates scanning, vocabulary discovery, annotation, propagation, and validation to specialized subagents, then manages batching, persistence, retries, coverage gates, and final reporting.

## When to Use

- Annotating a codebase with unit/dimension comments (e.g., `D18{tok}`, `D27{UoA/tok}`)
- Performing dimensional analysis on DeFi protocols, financial code, or scientific computations
- Hunting for arithmetic bugs caused by unit mismatches, missing scaling, or precision loss
- Auditing codebases with mixed decimal precisions or fixed-point arithmetic

## When NOT to Use

- Codebases with no numeric arithmetic or unit conversions — there is nothing to annotate
- Pure integer counting logic (loop indices, array lengths) with no physical or financial dimensions
- When you only need a quick spot-check of a single formula — read the code directly instead of running the full pipeline

## Execution Mode

This skill runs in one mode only: `full-auto`.
This is a workflow-based skill that delegates step-specific work to specialized agents via the `Task` tool. You orchestrate the overall process, manage coverage and state persistence, and ensure that every in-scope file is processed through each step of the pipeline.

- Always run the full pipeline in this order: Step 1 -> Step 2 -> Step 3 -> Step 4.
- The main skill context must not perform repository-wide dimensional analysis, annotation, propagation, or bug validation itself when a dedicated subagent exists for that step.
- The main skill context may inspect artifacts, manifests, and subagent outputs only as needed to route work, build prompts, persist state, and determine completion.
- Any mode argument provided by the caller is ignored.
- Report all results at the end in a single summary.

When you start a step, report it:

```text
Starting Step: Step {n}
```

## Scope and Coverage Guarantees

This skill must audit **all in-scope arithmetic files**, including large repositories.

- In-scope files are defined by Step 1 scanner output (`files` array), across **all** priority tiers (CRITICAL, HIGH, MEDIUM, LOW).
- If Step 1 narrows inputs for vocabulary discovery (for example, CRITICAL/HIGH only), that narrowing applies to discovery only. It **never** reduces annotation or validation scope.
- `arithmetic-scanner` persists the in-scope file manifest to `DIMENSIONAL_SCOPE.json` in the project root, and that manifest is the source of truth for Steps 2-4.
- A file is considered fully covered only when all three statuses are present:
  - `step2`: anchor annotation completed (or explicit no-anchor result)
  - `step3`: propagation completed (or explicit no-propagation result)
  - `step4`: validation completed
- `dimension-discoverer` persists the discovered dimensional vocabulary to `DIMENSIONAL_UNITS.md` in the project root for reuse by later steps and future runs.
- When a file ends in a terminal `BLOCKED` state, persist the blocking reason and retry count in `DIMENSIONAL_SCOPE.json` and reflect the same file in `coverage.unprocessed_files`.
- Do not finish while any in-scope file remains unprocessed in any step.

## Delegation Contract

- `arithmetic-scanner` owns repository scanning, arithmetic-file prioritization, and writing `DIMENSIONAL_SCOPE.json`.
- `dimension-discoverer` owns dimensional vocabulary discovery, unit inference, and writing `DIMENSIONAL_UNITS.md`.
- `dimension-annotator` owns annotation format decisions, anchor-point edits, and comment-writing behavior.
- `dimension-propagator` owns propagation logic, inferred annotations, and mismatch reporting during tracing.
- `dimension-validator` owns bug detection, red-flag evaluation, rationalization rejection, and confirmation or refutation of propagated mismatches.
- The main skill context must not substitute its own dimensional reasoning for skipped or unlaunched subagents. If a step requires specialized reasoning, launch the corresponding subagent.
- Use reference files as subagent support material. Pass them to the relevant step in prompts instead of treating them as instructions for the main skill context.

## Workflow

Follow these sections in order. Do not advance until the current step satisfies its completion gate.

### Shared Orchestration Rules

- `DIMENSIONAL_SCOPE.json` and `DIMENSIONAL_UNITS.md` live in the project root.
- The main skill context verifies Step 1 artifacts but does not write either Step 1 artifact itself.
- `DIMENSIONAL_SCOPE.json.in_scope_files` is the source of truth for Steps 2-4. Never derive later scope from discovery-only inputs.
- When a later step reaches terminal `BLOCKED`, persist the matching `step*_reason` and `step*_retry_count` fields on the file entry in `DIMENSIONAL_SCOPE.json`.
- `coverage.unprocessed_files` must be derived from terminal `BLOCKED` entries in `DIMENSIONAL_SCOPE.json` using `{ "path": "...", "blocked_step": "step2|step3|step4", "reason": "...", "retry_count": 1 }`.
- A step may retry a `BLOCKED` file once with a focused prompt. If it is still `BLOCKED`, keep the documented reason and continue. Do not finalize while any file remains `PENDING`.

### Step 1: Vocabulary and Scope Discovery

If cached artifacts cannot be reused, delegate repository scanning to `arithmetic-scanner` and vocabulary discovery to `dimension-discoverer`. Do not do that step-specific analysis directly in the main skill context.

1. Check whether `DIMENSIONAL_UNITS.md` and `DIMENSIONAL_SCOPE.json` already exist in the project root.
2. If both exist, read them and confirm:
   - `DIMENSIONAL_SCOPE.json.project_root` matches the current repo root
   - `DIMENSIONAL_SCOPE.json` contains `in_scope_files`, `discoverer_focus_files`, `recommended_discovery_order`, and per-file `step2`, `step3`, `step4` fields
   - `DIMENSIONAL_UNITS.md` is a usable dimensional vocabulary for this repo
3. If either artifact is stale, malformed, missing required structure, or clearly for another repo, discard reuse and rerun the rest of Step 1.
4. If both artifacts are valid, reuse them directly. If `in_scope_files` is empty, skip Steps 2-4 and produce final output with zero findings.
5. Otherwise use the `Task` tool to spawn the `arithmetic-scanner` agent. Its prompt must include:
   - project root path
   - absolute output path for `DIMENSIONAL_SCOPE.json`
   - instruction to write the Step 1 scope manifest to disk and return the same scope data in its report
6. The scanner owns Step 1 scope persistence. It must:
   - identify dimensional-arithmetic files and prioritize them as usual
   - write `DIMENSIONAL_SCOPE.json` with `project_root`, `in_scope_files`, `discoverer_focus_files`, and `recommended_discovery_order`
   - initialize every in-scope file with `step2: "PENDING"`, `step3: "PENDING"`, and `step4: "PENDING"`
   - still write an empty manifest when no arithmetic files are found
   - still narrow `discoverer_focus_files` to CRITICAL/HIGH when more than 50 arithmetic files are found, while keeping all priorities in `in_scope_files`
7. After the scanner completes, read `DIMENSIONAL_SCOPE.json` from disk and confirm it exists and contains the required Step 1 fields before continuing.
8. Use the `Task` tool to spawn the `dimension-discoverer` agent. Its prompt must include:
   - project root path
   - absolute path to `DIMENSIONAL_SCOPE.json`
   - absolute output path for `DIMENSIONAL_UNITS.md`
   - prioritized `discoverer_focus_files` with each file's path, priority, score, and category
   - `recommended_discovery_order`
9. The discoverer owns Step 1 vocabulary persistence. It must read `DIMENSIONAL_SCOPE.json` as the Step 1 source of truth and write `DIMENSIONAL_UNITS.md` with `Base Units`, `Derived Units`, and `Precision Prefixes` sections. If `in_scope_files` is empty, it must still write the same