Direction Picker
nexu-io/open-design
Resolves the visual direction at the plan stage from the brief and design system, without asking the user.
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.
$ npx skills add frenzymath/Danus --skill direct-proving -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install frenzymath/Danus direct-proving --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agents/skills/worker/direct-proving .claude/skills/direct-proving && rm -rf skills-srcUse ~/.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/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .claude/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-provingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add frenzymath/Danus --skill direct-proving -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install frenzymath/Danus direct-proving --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agents/skills/worker/direct-proving .agents/skills/direct-proving && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .agents/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add frenzymath/Danus --skill direct-proving -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install frenzymath/Danus direct-proving --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agents/skills/worker/direct-proving .cursor/skills/direct-proving && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .cursor/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/frenzymath/Danus.git --path agents/skills/worker/direct-proving--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add frenzymath/Danus --skill direct-proving -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install frenzymath/Danus direct-proving --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agents/skills/worker/direct-proving .gemini/skills/direct-proving && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .gemini/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install frenzymath/Danus direct-provingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add frenzymath/Danus --skill direct-proving -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .github/skills && cp -r skills-src/agents/skills/worker/direct-proving .github/skills/direct-proving && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .github/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add frenzymath/Danus --skill direct-proving -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install frenzymath/Danus direct-proving --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/frenzymath/Danus.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agents/skills/worker/direct-proving .opencode/skills/direct-proving && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "direct-proving" agent skill from https://github.com/frenzymath/Danus/tree/codex/agents/skills/worker/direct-proving into .opencode/skills/direct-proving/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "direct-proving", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
direct-provingScreen 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.
Direct Proving is an agent skill from 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. Use when a decomposition plan is created.
Its SKILL.md is about 1.3k 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.
12 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 6d92e8d. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Direct Proving loads about 1.3k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 643 words of instructions outside code blocks.
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.
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.
The full file from frenzymath/Danus at commit 6d92e8d, republished under its Apache-2.0 licence (© frenzymath). 643 words, ~1,291 tokens.
.claude/skills/direct-proving/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Use this skill to screen decomposition plans by first trying to carry the whole plan through, and if it does not fully go through, then identify the key stuck points.
Read:
subgoalsimmediate_conclusions, toy_examples, counterexamples, and failed_paths$construct-counterexamples for that subgoal — test whether it is false, too strong, or missing hypotheses (not merely hard). If no counterexample emerges and the subgoal still resists after at least two genuine direct attempts, do not grind indefinitely: record the stuck point as an obstacle/dead_end finding (gm_add) so siblings skip it and the next round's master_guidance can bring fresh direction.$verify-proof in partial-candidate mode before treating it as established. Adopting unverified partial results as building blocks is the single biggest correctness risk; the verifier is the sole authority on whether the partial result really holds.Publish one record per attempted subgoal to global memory with gm_add (kind
proof_attempt): claim = the subgoal + its status, evidence = the attempt /
the partial proof if solved, plus these fields:
{
"plan_id": "...",
"attempt_type": "direct",
"subgoal": "...",
"attempt_summary": "...",
"status": "solved|partial|stuck",
"used_examples": ["..."],
"used_counterexamples": ["..."],
"counterexample_search_for_stuck_subgoal": {
"performed": true,
"summary": "...",
"result": "refuted|not_refuted|inconclusive|not_needed"
},
"key_stuck_points": ["..."],
"used_results": ["..."],
"adapted_from": ["relevant statements or proofs whose ideas were migrated"],
"migration_failures": ["why a proof adaptation or migration failed"],
"branch_id": "optional"
}Record the plan's updated status (screening / screened / solved) in your
local memory or as a follow-up plan finding.
gm_add (publish the proof-attempt finding)gm_search (recall examples, counterexamples, dead-ends, and verified facts)fact_submit (verify any self-contained partial result before building on it; see $verify-proof)search_arxiv_theoremsIf a decomposition plan does not solve the problem directly after attempting all of its subgoals, publish a dead_end finding (gm_add) that summarizes the plan-local stuck points and any important proof-migration failures, so siblings skip them.
© 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
SKILL.md and 1 other file in agents/skills/worker/direct-proving of frenzymath/Danus.
Open the folder on GitHubat commit 6d92e8d
Direct Proving 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Direct Proving this skillfrenzymath/Danus | 476 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Direction Pickernexu-io/open-design | 100k | — | ~472 | Automated safety check: Warn | Apache-2.0 | |
| Frontend Design Directionaffaan-m/ECC | 276k | 1 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Direction Attributethedaviddias/Front-End-Checklist | 74k | — | ~534 | Automated safety check: Pass | MIT | |
| Bio Crispr Screens Screen QcFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | — | ~2.1k | Automated safety check: Pass | None | |
| Screen Recordinggithub/awesome-copilot | 40k | — | ~2k | Automated safety check: Pass | MIT |
nexu-io/open-design
Resolves the visual direction at the plan stage from the brief and design system, without asking the user.
affaan-m/ECC
Set an ECC-specific frontend design direction for production UI work.
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing templates, rendered HTML, or shared components related to Set text direction for RTL languages.
FreedomIntelligence/OpenClaw-Medical-Skills
Quality control for pooled CRISPR screens. An agent skill from FreedomIntelligence/OpenClaw-Medical-Skills.
github/awesome-copilot
Create annotated animated GIF demos and screen recordings for pull requests and documentation.
sickn33/agentic-awesome-skills
macOS screen recorder that captures the main display PLUS system audio via ScreenCaptureKit — no BlackHole/loopback driver, no sudo, just the standard Screen Recording permission.
frenzymath/Danus
Validate externally referenced theorems by querying arXiv theorem search first and Codex's built-in web search second.
frenzymath/Danus
Construct candidate counterexamples to test a proposed conjecture, lemma, or intermediate claim by keeping the assumptions true while making the claimed conclusion fail.
frenzymath/Danus
Generate and analyze simpler examples that satisfy both the assumptions and the conclusion of a theorem statement or subgoal.
frenzymath/Danus
Synthesize the common stuck points across failed decomposition plans.
frenzymath/Danus
Derive immediate mathematical consequences from a theorem statement or subgoal.
frenzymath/Danus
Propose multiple subgoal decomposition plans for the current theorem using the information already gathered.
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. Direct Proving is an agent skill from 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.
Direct Proving fits situations like: A decomposition plan is created.
Run `npx skills add frenzymath/Danus --skill direct-proving -a claude-code`. Or copy the skill folder (agents/skills/worker/direct-proving in frenzymath/Danus) into .claude/skills/direct-proving in your project. Claude Code loads it when a task matches its description.
Run `npx skills add frenzymath/Danus --skill direct-proving -a codex`. Or copy the skill folder (agents/skills/worker/direct-proving in frenzymath/Danus) into .agents/skills/direct-proving in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add frenzymath/Danus --skill direct-proving -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/direct-proving, .gemini/skills/direct-proving, .github/skills/direct-proving and .opencode/skills/direct-proving in your project.
SKILL.md names no scripts, command-line tools or credentials: Direct Proving is instructions for the agent only.
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.
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.
Direct Proving 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.
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Direct Proving: Direction Picker (nexu-io/open-design, 100k stars), Frontend Design Direction (affaan-m/ECC, 276k stars), Direction Attribute (thedaviddias/Front-End-Checklist, 74k stars) and Bio Crispr Screens Screen Qc (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.