Agent skill

Verify Proof

by frenzymath in frenzymath/Danus

Verify a result and, on acceptance, write it as a fact — via the factsubmit tool.

Apache-2.0Auto-check passed

Install Verify Proof

skills CLI
$ npx skills add frenzymath/Danus --skill verify-proof -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install frenzymath/Danus verify-proof --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agents/skills/worker/verify-proof .claude/skills/verify-proof && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
verify-proof
GitHub stars
475
Token cost
~1.4k tokens
SKILL.md length
738 words
Files
2
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

Verify a result and, on acceptance, write it as a fact — via the factsubmit tool.

  • The full target theorem AND for every sharply-delimited intermediate result
  • SKILL.md covers When to submit, Before you submit — write an…, Submit and repair and The verifier is the only…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Formula you intend to build on

What it does

Verify Proof is an agent skill from frenzymath/Danus. Verify a result and, on acceptance, write it as a fact — via the factsubmit tool. Use for the full target theorem AND for every sharply-delimited intermediate result, lemma, construction, or formula you intend to build on. The verifier is the sole authority on mathematical correctness.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

The repository describes itself as: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory. The licence is Apache-2.0.

When your agent uses it

  • The full target theorem AND for every sharply-delimited intermediate result
  • Formula you intend to build on

Example prompts

  • “/verify-proof”

What it can do on your machine

Read from SKILL.md and the folder at commit 6d92e8d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Verify Proof loads about 1.4k tokens when it runs. Until then it costs about 75 tokens; SKILL.md has 738 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from frenzymath/Danus at commit 6d92e8d, republished under its Apache-2.0 licence (© frenzymath). 738 words, ~1,415 tokens.

Download SKILL.mdSave it as .claude/skills/verify-proof/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
verify-proof
description
Verify a result and, on acceptance, write it as a fact — via the fact_submit tool. Use for the full target theorem AND for every sharply-delimited intermediate result, lemma, construction, or formula you intend to build on. The verifier is the sole authority on mathematical correctness.

Verify Proof

The verifier is the canonical and sole authority on mathematical correctness. Mathematics requires 100% accuracy; even though this verifier is not a formal proof assistant, it is the strongest correctness check in the system. No LLM consultation, panel, or self-critique substitutes for it.

You verify and write a fact through one tool: fact_submit. It runs the glossary-coverage check, calls the verifier, and writes the fact to the fact graph iff the verifier accepts — there is no other way a fact enters the graph.

When to submit

  • The full target theorem — when you have assembled a complete proof of the whole problem (as a self-contained statement + proof, citing its predecessors by fact_id).
  • Every intermediate result you intend to USE downstream — a lemma, a candidate construction, an arithmetic/closed-form claim, a saturation or local-to-global claim, any sharply-delimited step. Adopting an unverified partial result as a building block is the single biggest correctness risk. When in doubt, submit.

Choose a substantive mathematical boundary, not the smallest checkable line. Routine calculations, substitutions, and bookkeeping identities should normally remain internal steps in the proof of a deeper fact. The submitted fact should state one mathematically significant conclusion; depth must not be simulated by bundling several shallow or unrelated claims. Split supporting claims only when they have independent downstream uses, separate proof obligations, or need isolated verifier repair.

Do not build on an unverified finding from global memory. A conclusion / example / counterexample there is awareness, not a brick — re-derive it as a self-contained statement+proof and submit it before relying on it.

Before you submit — write an "ugly-proof" fact

A fact in the fact graph is written in "ugly-but-rigorous" form (the operator may call it an "ugly-proof"). The one goal of this form is that the fact is mechanically checkable for correctness by a reader with no memory and no math intuition (an agent with no recall, a human, the verifier). It is allowed — encouraged — to be ugly: redundant, machine-flavored, verbose. It is not allowed to be ambiguous, vague, or context-dependent. "Ugly" is the deliberate contrast with the polished arXiv paper (a separate pipeline); here, only mechanical correctness matters.

Concretely, before you submit:

  • Self-contained. A reader using only this fact + its declared predecessors + the project glossary can decide whether the math is correct. No appeal to chart positions, parse status, project history, or "as we know".
  • Define every symbol. Each symbol used in the statement/proof is defined: in this fact's glossary_introduces, in a cited predecessor's glossary, in the project glossary, or in the global glossary of universal notation (Z, Q, R, C, floor/ceil, gcd/lcm, intervals, Greek parameter names). Don't redefine universal notation — glossary_introduces is for project-specific symbols only. Reuse the project's existing symbol for the same object. fact_submit returns undefined_symbols if you missed one.
  • Cite every dependency by fact_id — never "by the result above", never the problem statement as a math source.
  • Every quantifier explicit; every introduced parameter (epsilon, k, …) carries an explicit range.
  • No handwave ("obviously", "easy to see", "routine", "analogously", "by some classical argument") and no chart-position references ("as above").
  • Avoid duplicates. gm_search the fact graph / global memory (or read fact_graph/facts/) for an existing fact with the same statement; if one exists, cite its fact_id instead of re-proving it.
Show full SKILL.md (203 more words)Show less

Submit and repair

Call fact_submit(statement, proof, predecessors=[...], glossary_introduces={...}). Read the result:

  • accepted: true, fact_id — the fact is written. Cite fact_id downstream.
  • accepted: false, repair_hints (+ undefined_symbols) — revise: resolve critical errors first, then all remaining gaps; do not assume the fix is local — change strategy or backtrack if needed; then resubmit. Treat any wrong verdict, any critical error, or any gap as failure.
  • verdict: "error" — the verify service was unavailable; retry.
  • accepted: true, write_error (e.g. a predecessor was revoked) — the fact was not written; re-prove or avoid that predecessor.

Every outcome is auto-logged to global memory (kind verification), so the feedback is shared — gm_search it to learn from others' rejections.

The verifier is the only correctness authority

If your own reasoning, the main agent's master_guidance, or any other LLM calls a result correct but fact_submit rejects it, the verifier wins. Always. Note the disagreement (a dead_end finding) and treat the "looks correct" opinion as the unreliable signal it was. A non-verifier opinion (including master_guidance) is for ideas and directions, never for correctness.

Tools

  • fact_submit (the only path to verify a result and write a fact)
  • gm_search (check for an existing fact before submitting; read others' verification outcomes)
  • the fact graph is read directly (fact_graph/facts/, glossary.json)

© frenzymath, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in agents/skills/worker/verify-proof of frenzymath/Danus.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 6d92e8d

Compare with similar skills

Verify Proof next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Verify Proof compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Verify Proof this skillfrenzymath/Danus475—~1.4kAutomated safety check: PassApache-2.0
Proof Videoopenclaw/openclaw392k—~2.4kAutomated safety check: PassMIT
QA Acceptancepaperclipai/paperclip99k—~964Automated safety check: PassMIT
Fact Check X Unifiedsickn33/agentic-awesome-skills47k1 repos~1.7kAutomated safety check: PassApache-2.0
Fact Check X Completesickn33/agentic-awesome-skills47k1 repos~2.3kAutomated safety check: PassApache-2.0
Fact CheckTHU-MAIC/OpenMAIC40k—~1.9kAutomated safety check: WarnMIT

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  • Construct Toy Examples

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    475 GitHub stars~541 tokensUpdated 1 mo ago
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  • Direct Proving

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    Screen a decomposition plan by first trying to prove all of its subgoals directly, then identifying the key stuck points if the plan does not fully go through.

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  • Identify Key Failures

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    Synthesize the common stuck points across failed decomposition plans.

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  • Derive immediate mathematical consequences from a theorem statement or subgoal.

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Questions about Verify Proof

What does Verify Proof do?

Verify a result and, on acceptance, write it as a fact — via the factsubmit tool. Verify Proof is an agent skill from frenzymath/Danus. Verify a result and, on acceptance, write it as a fact — via the factsubmit tool.

When should I use Verify Proof?

Verify Proof fits situations like: the full target theorem AND for every sharply-delimited intermediate result; formula you intend to build on.

How do I install Verify Proof in Claude Code?

Run `npx skills add frenzymath/Danus --skill verify-proof -a claude-code`. Or copy the skill folder (agents/skills/worker/verify-proof in frenzymath/Danus) into .claude/skills/verify-proof in your project. Claude Code loads it when a task matches its description.

How do I install Verify Proof in Codex?

Run `npx skills add frenzymath/Danus --skill verify-proof -a codex`. Or copy the skill folder (agents/skills/worker/verify-proof in frenzymath/Danus) into .agents/skills/verify-proof in your project. Codex loads it when a task matches its description.

Can I use Verify Proof in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add frenzymath/Danus --skill verify-proof -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/verify-proof, .gemini/skills/verify-proof, .github/skills/verify-proof and .opencode/skills/verify-proof in your project.

What does Verify Proof need to run?

SKILL.md names no scripts, command-line tools or credentials: Verify Proof is instructions for the agent only.

Does Verify Proof access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Verify Proof safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Verify Proof use?

Verify Proof is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Verify Proof use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Verify Proof?

Skills that share tags, products or a category with Verify Proof: Proof Video (openclaw/openclaw, 392k stars), QA Acceptance (paperclipai/paperclip, 99k stars), Fact Check X Unified (sickn33/agentic-awesome-skills, 47k stars) and Fact Check X Complete (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Verify Proof?

frenzymath (a GitHub organization) maintains it in frenzymath/Danus, which has 475 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on August 27, 2026.

Source: frenzymath/Danus on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.