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.
curl -O https://raw.githubusercontent.com/helicerat/llm-wiki-loop/main/.claude/skills/wiki-measure/SKILL.mdgit clone --depth 1 https://github.com/helicerat/llm-wiki-loopWrote 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.
[](https://agentmods.dev/skills/helicerat/llm-wiki-loop/wiki-measure)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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:
candidateandn >= 3and the outcomes support it →rulecandidateandn >= 3and the outcomes do not support it → stayscandidate, and record why in the page bodyruleand 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
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.
- 9d ago First seen · 74 lines · 69 tokens per session scan A c469c8cf0194
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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