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.
npx agentmods add commands/frenzymath/archon/formalizegit clone --depth 1 https://github.com/frenzymath/ArchonWrote 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/commands/frenzymath/archon/formalize)<a href="https://agentmods.dev/commands/frenzymath/archon/formalize"><img src="https://agentmods.dev/badge/commands/frenzymath/archon/formalize.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.02459 |
| Opus 5 | $0.00005 | $0.01229 |
| Sonnet 5 | $0.00002 | $0.00492 |
| Haiku 4.5 | $0.00001 | $0.00246 |
Grade A, and why
formalize 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 4d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lean4 Formalize
Interactive formalization: draft Lean skeletons from informal claims, then prove them with guided cycles. Combines /lean4:draft and /lean4:prove in a single human-in-the-loop workflow.
Compatibility: Accepts all flags from old formalize (v4.3.x). Semantics are broader — new formalize runs a full prove cycle after drafting. Users wanting the old lighter-weight "draft + shallow proof attempt" behavior should use /lean4:draft --mode=attempt. Users wanting skeletons only should use /lean4:draft.
Usage
/lean4:formalize "Every continuous function on a compact set is bounded"
/lean4:formalize --rigor=axiomatic "Zorn's lemma implies AC"
/lean4:formalize --source ./paper.pdf # Ingest, pick claims, formalize
/lean4:formalize --source ./paper.pdf "Theorem 3.2" # Source as context, topic as claim
/lean4:formalize --output=file --out=MyTheorem.lean "..."
Inputs
| Arg | Required | Default | Description |
|---|---|---|---|
| topic | no | — | Informal claim to formalize. Optional when --source provides it (source-led flow). At least one of topic or --source must be given; omitting both is a hard error. |
| --rigor | no | checked |
checked | sketch | axiomatic |
| --verify | no | best-effort |
best-effort | strict. Verification strictness for key claims. See learn-pathways.md. |
| --level | no | intermediate |
beginner | intermediate | expert |
| --output | no | chat |
chat | scratch | file |
| --out | no | — | Output path. Required when --output=file; hard error if missing. |
| --overwrite | no | false |
Allow overwriting existing files with --output=file. Without flag, existing target → hard error. |
| --source | no | — | File path, URL, or PDF to seed formalization. See learn-pathways.md. |
| --intent | no | math |
auto | usage | math. See learn-pathways.md. |
| --presentation | no | auto |
informal | supporting | formal | auto. Controls user-facing display, not Lean backing. See learn-pathways.md. |
| --claim-select | no | — | first | named:"..." | regex:"...". Noninteractive claim selection from --source. |
| --draft-mode | no | attempt |
skeleton | attempt. Mode for the draft phase (default is attempt in formalize context). |
| --draft-elab-check | no | best-effort |
best-effort | strict. Elaboration check for the draft phase. |
| --deep | no | never | never | ask | stuck | always. Deep mode for prove phase. |
| --deep-sorry-budget | no | 1 | Max sorries per deep invocation |
| --deep-time-budget | no | 10m | Max time per deep invocation |
| --commit | no | ask | ask | auto | never |
| --golf | no | prompt | prompt | auto | never |
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.
- 4d ago First seen · 163 lines · 11 tokens per session scan A 7743507e6664
formalize is a command published in the GitHub repository frenzymath/Archon (213 stars, last pushed 17d ago), licensed Apache-2.0. It adds 11 tokens to every session and 2,459 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
derive
Save a clean reference derivation of a target equation or theorem to derivations/. Draws from course materials (textbook, lecture notes) rather than testing the user.
teach
Narrated, watch-along network analysis in Gephi for teaching and demos.
afsim-learn
Command "afsim-learn" from qingzhoupro/afsim-skill, covering /afsim-learn — 文档解析融入 skill, 使用方式, 方式一：提供文件路径, 方式二：直接粘贴文档内容 and 方式三：指定分类.
openehr-explain
One-stop router that explains or looks up any openEHR thing — auto-detects an archetype, a template, an RM/AM/BASE type, an RM structural concept, an ADL idiom, an AQL query or keyword, or a terminology code (replaces /archetype-explain, /template-explain, /type-spec, /rm-structure, /adl-idiom, /terminology).
thesis
Plan, structure, or strengthen a PhD/research thesis or dissertation in AEC.
talk
Turn a paper (or several) into an academic talk — outline, slides, speaker notes, backups, rehearsal plan.