Agent skill

Search Math Results

by frenzymath in frenzymath/Danus

Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references.

Apache-2.0Auto-check passed

Install Search Math Results

skills CLI
$ npx skills add frenzymath/Danus --skill search-math-results -a claude-code

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

GitHub CLI
$ gh skill install frenzymath/Danus search-math-results --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/search-math-results .claude/skills/search-math-results && 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
search-math-results
GitHub stars
476
Token cost
~3k tokens
SKILL.md length
1,430 words
Files
2
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references.

  • Works in 12 steps: Identify the current program_stage,… → For non-blocker modes, usually generate… → Start with search_arxiv_theorems. → …
  • The current active program needs repair
  • SKILL.md covers Input Contract, Search Modes, Procedure and Usefulness Test, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Search Math Results is an agent skill from frenzymath/Danus. Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references. Use when the current active program needs repair, mutation, analogy, a program shift, or carefully gated obstruction search.

Its SKILL.md is about 3k 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 current active program needs repair
  • A program shift
  • Carefully gated obstruction search

Example prompts

  • “/search-math-results”

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. Identify the current program_stage, active_program, missing_mechanism, and search_mode before searching.
  2. For non-blocker modes, usually generate searches in multiple layers. In fresh_orientation, allow broad object-level, theorem-level…
  3. Start with search_arxiv_theorems.
  4. When using search_arxiv_theorems, phrase the query as a complete mathematical statement whenever possible, but also issue mechanism- and…
  5. Inspect the returned items and decide whether they are useful for the current active program.
  6. Do not use broad recursive scans of downloads/ as a theorem-search engine. If an exact local paper/file is already known or…
  7. If a genuinely new technical branch is opened (a new class of objects, a new construction regime, or a new body of machinery), then before…
  8. External search first is still the default, but once a genuinely new direction is chosen, exact paper download/read is expected before…
  9. Keep all downloaded PDFs and extracted text files organized inside downloads/ in the current working directory.
  10. If a useful theorem/example/counterexample is found and it comes from a paper, download that paper into the workspace, extract its text…
  11. If a useful theorem is found, do not stop at the statement alone. Read the proof of that theorem as well and extract any techniques…
  12. Expand the definitions and concepts appearing in that theorem using the surrounding context of the paper, and check carefully whether the…

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 (its code samples are json).

    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

Search Math Results loads about 3k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 1,430 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~3k

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). 1,430 words, ~3,000 tokens.

Download SKILL.mdSave it as .claude/skills/search-math-results/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
search-math-results
description
Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references. Use when the current active program needs repair, mutation, analogy, a program shift, or carefully gated obstruction search.

Search Math Results

Use this skill as the default retrieval workflow for mathematical background and related results, conditioned on the live research program currently being pursued.

Input Contract

Read:

  • the current target statement, subgoal, lemma, or claim
  • the program_stage, chosen from:
    • fresh_orientation
    • active_program
    • mature_subproblem
  • the current active_program, meaning the live research program currently being pursued, such as a construction route, globalization route, mutation route, or other proof strategy
  • the current missing_mechanism, meaning the specific mechanism, construction, lemma, bridge, or proof move that is missing
  • the search_mode, chosen from:
    • repair
    • mutation
    • analogy
    • program_shift
    • theorem_level_blocker
  • the search intent:
    • theorem
    • construction
    • example
    • counterexample
    • background
  • relevant branch/subgoal context from memory

If the prompt explicitly declares the program_stage, active_program, missing_mechanism, or blocker policy, obey those declarations. If the prompt does not declare the stage, default to fresh_orientation for a new problem, first-pass search, or no mature program yet; use active_program when the run already has a live named program, branch, or missing mechanism; and use mature_subproblem only when the run is already narrowed to a repeatedly failed mature subproblem or mature active program.

Search Modes

  • repair: search for results or constructions that directly repair a specific missing step in the current active program.
  • mutation: search for nearby constructions or variants that modify the current active program while preserving continuity with it.
  • analogy: search broadly, including in apparently unrelated areas, for mechanisms, lemmas, constructions, examples, or proof ideas that might transfer to the current missing mechanism after translation or modest modification.
  • program_shift: search for a genuinely new program after repeated failure of the current one, while explaining the possible splice point or bridge back to the current problem.
  • theorem_level_blocker: search for obstruction or impossibility results only under the activation rule below.

theorem_level_blocker is not a default mode. It is disallowed by default in fresh_orientation. It is allowed in mature_subproblem when the blocker search targets that narrowed mature subproblem or mature active program rather than the whole original goal. It is also allowed whenever the prompt explicitly asks for obstructions, impossibility results, blocker theorems, or negative evidence. If blocker mode is not allowed, downgrade to repair, mutation, analogy, or program_shift.

Broad and creative search is allowed. Do not restrict yourself to the surface vocabulary of the current problem or only the literal keywords in the prompt. Cross-field and apparently unrelated analogy search is acceptable when it targets the same missing mechanism. Theorem-level, proof-level, theory-level, and more abstract analogy search are all allowed when tied to a plausible transfer idea.

Procedure

  1. Identify the current program_stage, active_program, missing_mechanism, and search_mode before searching.
  2. For non-blocker modes, usually generate searches in multiple layers. In fresh_orientation, allow broad object-level, theorem-level, proof-pattern, and theory-pattern queries. In active_program and mature_subproblem, still allow broad queries, but tie them to the active program or a plausible program shift.
  3. Start with search_arxiv_theorems.
  4. When using search_arxiv_theorems, phrase the query as a complete mathematical statement whenever possible, but also issue mechanism- and analogy-driven queries when they better target the missing mechanism. Each hit carries title, the full verbatim theorem text, arxiv_id, and the in-paper theorem_id; use arxiv_id to pull the exact paper.
  5. Inspect the returned items and decide whether they are useful for the current active program.
  6. Do not use broad recursive scans of downloads/ as a theorem-search engine. If an exact local paper/file is already known or prompt-recommended, read that exact path. Otherwise search externally first. If relevant long-term papers already exist in downloads/common, prefer those exact files before re-downloading.
  7. If a genuinely new technical branch is opened (a new class of objects, a new construction regime, or a new body of machinery), then before killing that branch normally do at least one of the following: download and read at least one exact paper about that direction; read an exact local paper already present in downloads/common or another exact prompt-recommended path; or explicitly justify why no extra literature layer is needed because the branch has already reduced to a previously audited regime.
  8. External search first is still the default, but once a genuinely new direction is chosen, exact paper download/read is expected before final branch rejection. This rule is about depth of engagement with a new direction: use a small number of exact relevant papers, not no papers and not many-paper rummaging.
  9. Keep all downloaded PDFs and extracted text files organized inside downloads/ in the current working directory.
  10. If a useful theorem/example/counterexample is found and it comes from a paper, download that paper into the workspace, extract its text, and read the extracted text before relying on the result.
  11. If a useful theorem is found, do not stop at the statement alone. Read the proof of that theorem as well and extract any techniques, constructions, reductions, or proof patterns that may help with the current target statement.
  12. Expand the definitions and concepts appearing in that theorem using the surrounding context of the paper, and check carefully whether the theorem is actually applicable to the current situation. Be explicit about terminology that may shift across contexts. If the theorem is only a partial result for the current target, also analyze why its method does not prove the full statement — which extra hypotheses it needs, where the proof breaks without them, and what obstruction this reveals (do not merely force the current object to satisfy the extra hypotheses).
  13. Record not only what the theorem says, but also what its proof suggests for the current active program and missing mechanism.
  14. If the theorem search returns no useful information, switch to Codex's built-in web search.
  15. Use the built-in web search either to look for specific math results or to gather background information, terminology, standard references, canonical constructions/examples/counterexamples, or remote analogies.
  16. If the built-in web search reveals a useful paper, again download it, extract its text, and read the relevant extracted text before using it in reasoning.
  17. If the built-in web search reveals a useful theorem, also read its proof, expand its local definitions from the paper context, and extract the techniques that look adaptable to the current active program. Apply the same partial-result analysis if the web result is only a partial result.
  18. Summarize the most useful findings and explain why they matter for the current proof state.
  19. If a result may later be used in a proof, preserve its full statement and source identifiers (title, authors, arxiv_id, theorem_id, year) so downstream proof steps can cite it explicitly — and so it can be passed as a structured external_refs entry when the proof that uses it is submitted via fact_submit.
Show full SKILL.md (334 more words)Show less

Usefulness Test

For fresh_orientation, treat search results as useful if they do at least one of the following:

  • provide a theorem/lemma/definition close to the target statement
  • provide a construction/example/counterexample that can be adapted
  • suggest a standard technique or reformulation relevant to the current branch or problem
  • provide a proof-level analogy
  • provide a theory-level analogy
  • provide a remote analogy together with a plausible transfer idea

For active_program, treat search results as useful if they do at least one of the following:

  • repair a concrete missing mechanism in the active program
  • provide a mutation of the current program
  • provide a remote analogy that can plausibly transfer
  • provide a new program together with a plausible splice point or bridge to the current problem
  • provide a proof-pattern or theory-pattern transfer hypothesis that could plausibly be migrated into the active program

For mature_subproblem, use the active_program criteria and additionally allow gated blocker search.

A result can be strategically useful even if it does not yet directly repair the missing mechanism, provided it includes a plausible transfer hypothesis explaining how its construction, proof, or theory might transfer.

Treat results as not useful if they are vague, merely generic survey material, or a whole-goal obstruction search when blocker mode is not allowed. If the results are too weak to guide the next step, fall back to the built-in web search.

Output Contract

Note a summary of the search in your local memory (events) — search is process, not a shared finding. (A useful reference you actually use is recorded inside the proof step that cites it, with its complete statement + paper_id/theorem_id/ arXiv id.) Summary record:

json
{
  "event_type": "search_math_results",
  "query": "...",
  "program_stage": "fresh_orientation|active_program|mature_subproblem",
  "active_program": "...",
  "missing_mechanism": "...",
  "search_mode": "repair|mutation|analogy|program_shift|theorem_level_blocker",
  "blocker_search_allowed": false,
  "usefulness_tier": "direct|strategic|discard",
  "analogy_depth": "theorem|proof|theory|meta",
  "transfer_hypothesis": "optional plausible transfer idea; analogy_depth is descriptive bookkeeping, not a ranking of importance",
  "new_direction_requires_exact_paper": false,
  "literature_depth_reached": "none|local_exact|downloaded_exact",
  "search_intent": "theorem|construction|example|counterexample|background",
  "primary_tool": "search_arxiv_theorems",
  "fallback_used": false,
  "splice_point": "optional bridge back to the current problem",
  "results_summary": ["..."],
  "useful_references": [
    {
      "title": "...",
      "complete_statement": "...",
      "url_or_id": "...",
      "paper_id": "...",
      "arxiv_id": "...",
      "theorem_id": "...",
      "local_pdf_path": "optional",
      "local_text_path": "optional",
      "expanded_definitions": ["paper-context expansions of terms/concepts used in the statement"],
      "applicability_check": ["why the statement does or does not apply in the current setting"],
      "partial_result_analysis": ["if only a partial result: extra hypotheses, where the method fails for the full problem, and what difficulty this reveals"],
      "proof_insights": ["optional extracted techniques or ideas from the proof"],
      "why_useful": "..."
    }
  ],
  "branch_id": "optional",
  "subgoal_id": "optional"
}

Tools

  • search_arxiv_theorems (Matlas arXiv theorem search — verbatim statements)
  • gm_search (check whether a sibling already found/used this result)
  • Codex built-in web search (fallback when the theorem search is too weak)
  • local memory (events) for the search log — direct file write

Failure Logging

If neither theorem search nor web search yields useful information, note in local memory (events):

  • event_type="search_math_results_stalled"
  • the attempted queries
  • the reason the results were not useful

© 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/search-math-results of frenzymath/Danus.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 6d92e8d

Compare with similar skills

Search Math Results 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.

Search Math Results compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Search Math Results this skillfrenzymath/Danus476—~3kAutomated safety check: PassApache-2.0
Mathparcadei/Continuous-Claude-v33.9k2 repos~1.6kAutomated safety check: NotesMIT
Math Computationtradecatlabs/vibe-coding-cn17k—~881Automated safety check: PassMIT
Rigorous Math Prooftradecatlabs/vibe-coding-cn17k—~571Automated safety check: PassMIT
Hunt Race Conditionsickn33/agentic-awesome-skills47k1 repos~5.7kAutomated safety check: PassMIT
Math Research Task Routertradecatlabs/vibe-coding-cn17k—~407Automated safety check: PassMIT

Similar skills

  • Math

    parcadei/Continuous-Claude-v3

    Unified math capabilities - computation, solving, and explanation.

    3.9k GitHub starsUsed in 2 repos~1.6k tokens
    Research & ScienceAuto-check: notes
  • Math Computation

    tradecatlabs/vibe-coding-cn

    Runs reproducible math computations and counterexample searches with SymPy, NumPy and mpmath, logging evidence without presenting results as proofs.

    17k GitHub stars~881 tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Rigorous Math Proof

    tradecatlabs/vibe-coding-cn

    Writes and audits natural-language math proofs as checkable packages, with explicit assumptions, proof obligations and counterexample hunting, refuting or repairing weak claims.

    17k GitHub stars~571 tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Hunt Race Condition

    sickn33/agentic-awesome-skills

    Hunting skill for race condition vulnerabilities. An agent skill from sickn33/agentic-awesome-skills.

    47k GitHub starsUsed in 1 repo~5.7k tokens
    DevelopmentAuto-check passed
  • Math Research Task Router

    tradecatlabs/vibe-coding-cn

    Routes an unclear math research request to exactly one specialist skill, naming the current stage, the reason, the inputs needed, a stop condition and the next step.

    17k GitHub stars~407 tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Math Derivation Auditor

    tradecatlabs/vibe-coding-cn

    Constructs honest, checkable derivation chains for formulas and theory notes, and keeps approximations and numerical hints from passing as rigorous proof.

    17k GitHub stars~429 tokensUpdated yesterday
    Research & ScienceAuto-check passed

More from frenzymath/Danus

All 16 skills in this repo
  • Validate externally referenced theorems by querying arXiv theorem search first and Codex's built-in web search second.

    476 GitHub stars~852 tokensUpdated 1 mo ago
    Auto-check passed
  • Construct candidate counterexamples to test a proposed conjecture, lemma, or intermediate claim by keeping the assumptions true while making the claimed conclusion fail.

    476 GitHub stars~790 tokensUpdated 1 mo ago
    Auto-check passed
  • Construct Toy Examples

    frenzymath/Danus

    Generate and analyze simpler examples that satisfy both the assumptions and the conclusion of a theorem statement or subgoal.

    476 GitHub stars~541 tokensUpdated 1 mo ago
    Auto-check passed
  • Direct Proving

    frenzymath/Danus

    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.

    476 GitHub stars~1.3k tokensUpdated 1 mo ago
    Auto-check passed
  • Identify Key Failures

    frenzymath/Danus

    Synthesize the common stuck points across failed decomposition plans.

    476 GitHub stars~586 tokensUpdated 1 mo ago
    Auto-check passed
  • Derive immediate mathematical consequences from a theorem statement or subgoal.

    476 GitHub stars~587 tokensUpdated 1 mo ago
    Auto-check passed

Questions about Search Math Results

What does Search Math Results do?

Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references. Search Math Results is an agent skill from frenzymath/Danus. Find program-conditioned math results, constructions, examples, counterexamples, analogies, and background references.

When should I use Search Math Results?

Search Math Results fits situations like: the current active program needs repair; A program shift; carefully gated obstruction search.

How do I install Search Math Results in Claude Code?

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

How do I install Search Math Results in Codex?

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

Can I use Search Math Results 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 search-math-results -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/search-math-results, .gemini/skills/search-math-results, .github/skills/search-math-results and .opencode/skills/search-math-results in your project.

What does Search Math Results need to run?

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

Does Search Math Results 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 Search Math Results 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 Search Math Results use?

Search Math Results 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 Search Math Results use?

About 3k tokens (SKILL.md is roughly 12k 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 Search Math Results?

Skills that share tags, products or a category with Search Math Results: Math (parcadei/Continuous-Claude-v3, 3.9k stars), Math Computation (tradecatlabs/vibe-coding-cn, 17k stars), Rigorous Math Proof (tradecatlabs/vibe-coding-cn, 17k stars) and Hunt Race Condition (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 Search Math Results?

frenzymath (a GitHub organization) maintains it in frenzymath/Danus, which has 476 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.