llm-wiki-loop: Skill for Claude Code

.claude/skills/wiki-measure/SKILL.md

wiki-measure is a skill for Claude Code from helicerat/llm-wiki-loop. It costs 69 tokens per session (698 once invoked), scanned A, original, MIT.

A workflow for recording what happened after a shipped artifact was checked, including the result and the claims that work supported.

In plain words
What is it for?
Use it after an artifact has been used and you have numbers, feedback, or another outcome to record. It appends the result to an outcomes log and updates related claims.
Why use it?
It prevents a project's records from treating untested assumptions as proven results.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is helicerat/llm-wiki-loop's own configuration. It tells Claude Code how to work on llm-wiki-loop itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything llm-wiki-loop configures →

Reuse

Borrowing it

Nothing to install: this file belongs to helicerat/llm-wiki-loop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/helicerat/llm-wiki-loop/main/.claude/skills/wiki-measure/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/helicerat/llm-wiki-loop

Made for: Claude Code.

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 wiki-measure

README.md
[![agentmods](https://agentmods.dev/badge/skills/helicerat/llm-wiki-loop/wiki-measure/github.svg)](https://agentmods.dev/skills/helicerat/llm-wiki-loop/wiki-measure)
Your own site
<a href="https://agentmods.dev/skills/helicerat/llm-wiki-loop/wiki-measure"><img src="https://agentmods.dev/badge/skills/helicerat/llm-wiki-loop/wiki-measure/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 wiki-measure

Your own site · 80×15
<a href="https://agentmods.dev/skills/helicerat/llm-wiki-loop/wiki-measure"><img src="https://agentmods.dev/badge/skills/helicerat/llm-wiki-loop/wiki-measure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 698 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 $0.00069 $0.00698
Opus 5 $0.00034 $0.00349
Sonnet 5 $0.00014 $0.00140
Haiku 4.5 $0.00007 $0.00070

Measured 9d ago against content hash c469c8cf0194, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

wiki-measure 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 9d 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.

.claude/skills/wiki-measure/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

wiki-measure

The operation everyone skips. Without it the wiki accumulates untested beliefs that read exactly like tested ones, and wiki-check degrades into superstition with good formatting.

Input

An artifact that shipped, and what happened to it. If the artifact was never run through wiki-check, say so — the claim list has to be reconstructed by hand and the attribution is weaker for it. Record that weakness in the entry rather than hiding it.

Steps

1. Append the outcome

One line to outcomes/outcomes.jsonl. Append only. Never edit a past entry; a correction is a new entry that references the old one.

{"id":"","date":"YYYY-MM-DD","artifact":"","claims":[],"result":{},"baseline":{},"note":""}

baseline is what the result is judged against. Fill it from your own history, never from someone else's peak — a comparison against an outlier you do not control teaches nothing.

2. Move n

For every claim in claims, increment n by exactly one and append the outcome id to the claim's outcomes list.

One artifact is one run. Three claims used in one piece of work get one increment each, not three. Splitting a single result into several confirmations is how a vault fakes its own evidence base.

Judge each claim against what it actually predicted. A claim that had nothing to say about this result is not incremented at all.

3. Apply transitions

Mechanical. No judgement, no exceptions:

  • candidate and n >= 3 and the outcomes support it → rule
  • candidate and n >= 3 and the outcomes do not support it → stays candidate, and record why in the page body
  • rule and the three most recent outcomes contradict it → retired, with the date and the three outcome ids

Never delete. A retired claim keeps its full history — the fact that something worked and then stopped is one of the few things a vault can know that a person cannot hold in memory.

4. Log

## [YYYY-MM-DD] measure | artifact -> outcome-id

What not to do

Read the full file on GitHub · 74 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. 9d ago First seen · 74 lines · 69 tokens per session scan A c469c8cf0194

Subscribe to this mod's changes

wiki-measure is a skill published in the GitHub repository helicerat/llm-wiki-loop (6 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 698 once invoked, about $0.0003 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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