Setting Up Papergraph
lotchuazzz-crypto/papergraph-mcp
A skill your agent uses when a user has cloned PaperGraph MCP and asks to install, initialize, configure, set up, or start using it with an agent or MCP client.
Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
$ npx skills add morluto/jacobian --skill decompose-mathematical-solution-corpora -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install morluto/jacobian decompose-mathematical-solution-corpora --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/morluto/jacobian.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .claude/skills/decompose-mathematical-solution-corpora && 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 "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .claude/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corporaType 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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install morluto/jacobian decompose-mathematical-solution-corpora --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/morluto/jacobian.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .agents/skills/decompose-mathematical-solution-corpora && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .agents/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install morluto/jacobian decompose-mathematical-solution-corpora --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/morluto/jacobian.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .cursor/skills/decompose-mathematical-solution-corpora && 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 "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .cursor/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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/morluto/jacobian.git --path .agents/skills/decompose-mathematical-solution-corpora--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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install morluto/jacobian decompose-mathematical-solution-corpora --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/morluto/jacobian.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .gemini/skills/decompose-mathematical-solution-corpora && 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 "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .gemini/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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 morluto/jacobian decompose-mathematical-solution-corporaInstalls 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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/morluto/jacobian.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .github/skills/decompose-mathematical-solution-corpora && 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 "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .github/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install morluto/jacobian decompose-mathematical-solution-corpora --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/morluto/jacobian.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/decompose-mathematical-solution-corpora .opencode/skills/decompose-mathematical-solution-corpora && 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 "decompose-mathematical-solution-corpora" agent skill from https://github.com/morluto/jacobian/tree/main/.agents/skills/decompose-mathematical-solution-corpora into .opencode/skills/decompose-mathematical-solution-corpora/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "decompose-mathematical-solution-corpora", 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.
decompose-mathematical-solution-corporaExtract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
Decompose Mathematical Solution Corpora is an agent skill from morluto/jacobian. Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/continuous-moves.md`).
It sits in Agent Workflows, covering Math and symbolic computation. It works with Model Context Protocol and Python. The repository describes itself as: Composable mathematics tools for agents. The licence is MIT.
Read from SKILL.md and the folder at commit 9dc2aaf. 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.
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.
Decompose Mathematical Solution Corpora loads about 1.9k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 37 tokens; SKILL.md has 977 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 morluto/jacobian at commit 9dc2aaf, republished under its MIT licence (© morluto). 977 words, ~1,924 tokens.
.claude/skills/decompose-mathematical-solution-corpora/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Extract reusable mathematical moves from a bounded solution corpus without turning the result into a file-by-file summary or a catalog of theorem wrappers. The unit of analysis is a method family: a recurring local mathematical move, its exact carrier, and the global reasoning that lifts it into a proof.
Use audit-mathematical-vocabulary for one bounded mathematical slice,
learn-from-math-agent-trajectories for one completed or paused investigation,
and audit-public-operation-contracts when a specific operation needs a deep
contract review. This skill owns the repository- or corpus-level decomposition
that precedes those focused audits.
Record the immutable revision of every source repository and the Jacobian revision and catalog used for comparison. Define the included directories, campaigns, or certificate families and any exclusions. Do not claim corpus closure from a partial clone, truncated artifact, generated summary, or unreadable dependency.
Inventory artifact types before reading deeply: papers and notes, Lean or other formal developments, exact Python or native programs, numerical experiments, solver encodings and proofs, prompts and trajectories, certificate bundles, test fixtures, and replay or publication metadata. Use the inventory to find method families, not to produce a chronological summary of every file.
Cluster sources by mathematical move rather than conjecture name or language. Examples include exact finite enumeration, dynamic programming, local-lemma witnesses, linear or semidefinite duality, algebraic elimination, interval enclosure, canonicalization, dependent rounding, coding-theoretic profiles, and finite-state transfer arguments.
Select representative sources from each family. Prefer sources that expose the local move, exact hypotheses, boundary behavior, and an independently replayable fixture. Continue sampling within a family until another representative no longer reveals a new carrier, postcondition, representation regime, or failure mode.
Describe the exact carrier, local move and stable postcondition, how the surrounding theorem uses it, and the evidence or fixture. Add representation, closure, and discovery details when they affect the proposed operation.
The local move is not automatically an operation. Reject boundaries that merely expose one loop iteration, solver control, callback, proof bookkeeping, or temporary data structure. Also reject the opposite boundary when it bundles the motivating theorem, search strategy, interpretation, and stopping rule. Look for one postcondition that remains meaningful if the surrounding paper or conjecture disappears.
Resolve the result's closure cases before calling it a complete finite value. Record the empty, zero, identity, repeated-root, singular, boundary, or continuum-locus case that applies to the proposed carrier. A result whose maximizers can be all points of a curve, for example, needs an exact locus variant rather than a fictitious complete finite witness list. This is part of the postcondition, not an implementation footnote.
For continuous or analytic sources, use the carrier checks to distinguish an exact local operation from a discretization that loses the source's decisive semantics.
Classify an established technique as a public-operation candidate, native-only function, private kernel, invariant or fixture, or caller reasoning. Technique names may be discovery vocabulary for a public operation without becoming separate operation IDs. Require an independently consumable postcondition before making an intermediate technique separately runnable.
Treat representation as mathematical execution evidence. State whether the carrier is materialized, succinct, generated, or oracle-backed; what expansion the implementation performs; whether that expansion is predictable before execution; and whether a compact representation changes the complexity class or output obligation.
Trace the local move to primary literature or an authoritative formal/library source. Verify the exact hypotheses, conclusion, conventions, algorithmic regime, and representation-sensitive complexity. Distinguish neighboring methods that share vocabulary but prove different guarantees. Use secondary surveys only to discover sources or terminology, then verify the conclusion against the primary source.
Research maintained exact backends and standard algorithms in proportion to the candidate. The question is whether a bounded, typed Jacobian contract is feasible—not whether the corpus's handwritten implementation should be copied. Record uncertainty when the literature supports the theorem but not an admissible exact kernel at the required scale.
Inspect the current catalog, native API, canonical values, request and result models, tests, admission decisions, and narrowly related issues. Attempt the smallest exact composition before declaring a gap. A manual coordinate change, cheap projection, or theorem-specific assembly normally remains caller work; incompatible values, detached certificates, or hidden expansion may instead identify an interoperability or contract problem.
Give every method family one disposition:
For operation candidates, state the semantic domain, stable postcondition, source representation, controlling work and output quantities, reconstruction or defining invariant, typed incomplete states, and at least one discriminating fixture. Separate the existence of a reusable gap from public-catalog admission.
Verify issue ownership narrowly before proposing a new issue. Reinforce the canonical owner when the operation, contract, or scale question is already in scope. Keep distinct semantics separate even when they share a backend. Do not file, comment, edit external systems, or make repository changes without user authorization.
Prefer compact in-thread findings and focused repository actions. Do not create large durable reports, copied source archives, or generated inventories unless the user requests them. Preserve only the small fixtures and evidence needed to replay a conclusion.
Stop when every inventoried method family has a disposition, every proposed operation has been compared with exact current composition and issue ownership, and additional representative sources yield no new local move, representation regime, postcondition, or fixture role. Report the frozen revisions, coverage, important exclusions, and unresolved uncertainties. “No gaps remain” means no unclassified reusable move within that declared scope, not that the corpus or mathematical literature contains nothing else.
Lead the final result with a compact technique-to-disposition matrix, followed by the few highest-value operation, contract, scale, and fixture actions. Keep the proof workflow separate from the atomic mathematical move throughout.
© morluto, MIT. 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 (references) in .agents/skills/decompose-mathematical-solution-corpora of morluto/jacobian.
Open the folder on GitHubat commit 9dc2aaf
Decompose Mathematical Solution Corpora 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 |
|---|---|---|---|---|---|---|
| Decompose Mathematical Solution Corpora this skillmorluto/jacobian | 205 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Setting Up Papergraphlotchuazzz-crypto/papergraph-mcp | 285 | — | ~3.3k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 64 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Fastmcp Client CLIPrefectHQ/fastmcp | 28k | 1 repos | ~823 | Automated safety check: Pass | Apache-2.0 | |
| MemPalace Setup and OperationMemPalace/mempalace | 59k | — | ~2.2k | Automated safety check: Pass | MIT |
lotchuazzz-crypto/papergraph-mcp
A skill your agent uses when a user has cloned PaperGraph MCP and asks to install, initialize, configure, set up, or start using it with an agent or MCP client.
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
shareAI-lab/learn-claude-code
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
PrefectHQ/fastmcp
Query and invoke tools on MCP servers using fastmcp list and fastmcp call.
MemPalace/mempalace
Installs and configures MemPalace as a private local palace, a shared-brain hub or a client of an existing hub, including MCP registration and version-correct initialization.
Tommy-yw/RunbookHermes
Build, test, inspect, install, and deploy MCP servers with FastMCP in Python.
morluto/jacobian
Evaluate Jacobian reliability using recently resolved conjectures as held-out probes.
morluto/jacobian
Author, package, validate, or run mathematical evaluations as Jacobian Harbor datasets.
morluto/jacobian
Design or audit a Jacobian operation’s mathematical contract, boundedness, exact results, and composition.
morluto/jacobian
Investigate MCP tool availability, discovery, and selection, including controlled adoption evaluations.
morluto/jacobian
Review mathematical agent trajectories for evidence-backed Jacobian improvements; do not resume solving.
morluto/jacobian
Design, audit, or repair mathematical benchmark verifiers, submission contracts, and scoring.
Works with
Categories
Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory. Decompose Mathematical Solution Corpora is an agent skill from morluto/jacobian. Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
Decompose Mathematical Solution Corpora fits situations like: tasks that involve Math and symbolic computation.
Run `npx skills add morluto/jacobian --skill decompose-mathematical-solution-corpora -a claude-code`. Or copy the skill folder (.agents/skills/decompose-mathematical-solution-corpora in morluto/jacobian) into .claude/skills/decompose-mathematical-solution-corpora in your project. Claude Code loads it when a task matches its description.
Run `npx skills add morluto/jacobian --skill decompose-mathematical-solution-corpora -a codex`. Or copy the skill folder (.agents/skills/decompose-mathematical-solution-corpora in morluto/jacobian) into .agents/skills/decompose-mathematical-solution-corpora 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 morluto/jacobian --skill decompose-mathematical-solution-corpora -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/decompose-mathematical-solution-corpora, .gemini/skills/decompose-mathematical-solution-corpora, .github/skills/decompose-mathematical-solution-corpora and .opencode/skills/decompose-mathematical-solution-corpora in your project.
SKILL.md names no scripts, command-line tools or credentials: Decompose Mathematical Solution Corpora is instructions for the agent only. Our summary lists: Python 3.
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.
Decompose Mathematical Solution Corpora is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 293 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Decompose Mathematical Solution Corpora: Setting Up Papergraph (lotchuazzz-crypto/papergraph-mcp, 285 stars), MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars) and Fastmcp Client CLI (PrefectHQ/fastmcp, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
morluto (a GitHub user) maintains it in morluto/jacobian, which has 205 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 5, 2026.
Source: morluto/jacobian on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.