Agent skill

Audit Mathematical Vocabulary

by morluto in morluto/jacobian

Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.

MITAuto-check passedResearch & Science

Install Audit Mathematical Vocabulary

skills CLI
$ npx skills add morluto/jacobian --skill audit-mathematical-vocabulary -a claude-code

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

GitHub CLI
$ gh skill install morluto/jacobian audit-mathematical-vocabulary --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/morluto/jacobian.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/audit-mathematical-vocabulary .claude/skills/audit-mathematical-vocabulary && 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
audit-mathematical-vocabulary
GitHub stars
220
Token cost
~1.5k tokens
SKILL.md length
781 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.

  • Works in 4 steps: Source demand. Use primary sources or… → Composition. Test whether producer… → Contract. Check accepted input, work and… → …
  • Tasks that involve Math and symbolic computation
  • SKILL.md covers Audit one slice, Classify before proposing work and Report the result
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Audit Mathematical Vocabulary is an agent skill from morluto/jacobian. Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Math and symbolic computation. It works with Model Context Protocol. The repository describes itself as: Composable mathematics tools for agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Math and symbolic computation

Example prompts

  • “/audit-mathematical-vocabulary”

Workflow steps

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

  1. Source demand. Use primary sources or established exact tasks to identify
  2. Composition. Test whether producer values can enter their natural
  3. Contract. Check accepted input, work and intermediate growth, output
  4. Backend feasibility. Check maintained exact backends for an appropriate

What it can do on your machine

Read from SKILL.md and the folder at commit 9dc2aaf. 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

Audit Mathematical Vocabulary loads about 1.5k tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 781 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 morluto/jacobian at commit 9dc2aaf, republished under its MIT licence (© morluto). 781 words, ~1,509 tokens.

Download SKILL.mdSave it as .claude/skills/audit-mathematical-vocabulary/SKILL.md (or your agent's skills folder).
name
audit-mathematical-vocabulary
description
Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.

Audit Mathematical Vocabulary

Find confirmed gaps in one mathematical slice without turning the audit into a backend-wrapper wishlist or a claim of complete coverage.

Use the relevant vocabulary model and domain references to assess the slice. Consult the admission contract when proposing publication or changing an execution envelope. Use audit-public-operation-contracts for a deep review of one operation and recent-conjecture-evaluations for a held-out conjecture evaluation.

Audit one slice

Choose one bounded slice, such as polynomial elimination. Name its mathematical boundary and the current-main revision. Do not silently expand it into a whole domain or repository audit.

Snapshot the relevant catalog facts before researching solutions. Record the operation IDs, owner domains, canonical inputs and outputs, natural downstream consumers, defining or reconstruction invariants, admitted bounds, and private backends. Use the live catalog and current source as authority; search results alone are not a complete inventory.

Check the slice through four independent lenses:

  1. Source demand. Use primary sources or established exact tasks to identify a finite mathematical obligation. State the needed result without importing the source's proof strategy. Literature recall or one bespoke workflow is not enough evidence for a public operation.
  2. Composition. Test whether producer values can enter their natural consumers unchanged after serialization. Include the empty, zero, singular, or identity case most likely to lose parent, axes, multiplicity, witness, or ambient context.
  3. Contract. Check accepted input, work and intermediate growth, output bounds, exact-result reconstruction, source binding, and typed failure behavior. Separate the semantic mathematical domain from the current execution envelope, and identify the quantities that actually control work and result size. A timeout, unavailable backend, or incomplete search is not a mathematical conclusion.
  4. Backend feasibility. Check maintained exact backends for an appropriate kernel only after establishing mathematical demand. Compare compact exact representations and algorithm regimes before treating a small fixed cap as necessary. Backend availability is evidence of feasibility, not evidence that Jacobian needs another public operation.

Prefer deterministic inspection and direct operation calls. Use an independent oracle when the finding depends on a mathematical value. Do not run model comparisons unless deterministic evidence cannot distinguish discovery from reasoning failure.

Show full SKILL.md (429 more words)Show less

Classify before proposing work

Assign each finding one primary class:

  • operation: the reusable mathematical postcondition is absent;
  • representation: the mathematical value cannot be expressed canonically;
  • interoperability: existing producers and consumers use incompatible values;
  • discovery: the operation exists but natural search does not surface it;
  • contract: the operation exists but its public semantics or evidence are insufficient;
  • scale/backend: the operation exists with the needed postcondition, but a coarse admission proxy, expanded representation, algorithm regime, or bounded implementation is the limiting factor;
  • reasoning: the needed vocabulary exists and the remaining failure is strategy selection or mathematical reasoning; or
  • no gap: the investigated path is already supported or does not justify a product change.

Before opening anything, search local reports and live issues and pull requests of every state for the mathematical family, operation IDs, and root mechanism. Treat an owned finding as ownership evidence, not a new issue. External issue, comment, or pull-request mutations still require explicit authorization.

A new gap is ready to file only when it has a stable mathematical postcondition, a plausible bounded exact implementation, useful composition with canonical values, concrete evidence beyond a single trace or backend API, and no existing owner. Lead the issue with the user or mathematical need, keep confirmed facts separate from hypotheses, and leave admission or implementation details open unless the evidence settles them.

When external issue creation is authorized, make the issue implementable rather than merely descriptive. Include the smallest discriminating exact fixture, the defining invariant or an independent oracle, the relevant degenerate or adversarial case, the preflight quantities that bound work and exact output, and explicit non-goals. For a repair, also state the existing owner and the smallest producer-consumer or public-contract regression. Do not invent a backend prescription when the evidence establishes only the postcondition.

Do not file a new operation solely because an existing operation rejects a large input. First determine whether predicted work, intermediate growth, and exact output remain small; whether a sparse, factored, modular, symbolic, or implicit representation avoids expansion; and whether a maintained backend or different exact algorithm materially widens the envelope. If so, record a scale/backend or admission gap against the existing postcondition.

Report the result

Report the slice and revision, evidence coverage, classified findings, ownership, and meaningful proof gaps. A valid audit may end with no gap. Propose another slice only when continued exploration is relevant to the request.

Persist a report when requested or needed for an ongoing audit campaign. Keep revision, slice, outcome, and ownership identifiable so later audits can check coverage; do not maintain a separate database for a few reports.

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

Files

Just SKILL.md in .agents/skills/audit-mathematical-vocabulary of morluto/jacobian.

Open the folder on GitHubat commit 9dc2aaf

Compare with similar skills

Audit Mathematical Vocabulary 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.

Audit Mathematical Vocabulary compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Audit Mathematical Vocabulary this skillmorluto/jacobian220—~1.5kAutomated safety check: PassMIT
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Read GitHubAgentTeam-TaichuAI/ScienceClaw6712 repos~638Automated safety check: PassNone
Proof Run Orchestratorwanshuiyin/Auto-claude-code-research-in-sleep17k1 repos~4.7kAutomated safety check: PassMIT
FirstdataMLT-OSS/FirstData184—~3.1kAutomated safety check: PassMIT
Fin Generate Ideacsmar432/finai-research109—~2.5kAutomated safety check: PassMIT

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Questions about Audit Mathematical Vocabulary

What does Audit Mathematical Vocabulary do?

Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review. Audit Mathematical Vocabulary is an agent skill from morluto/jacobian. Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.

When should I use Audit Mathematical Vocabulary?

Audit Mathematical Vocabulary fits situations like: tasks that involve Math and symbolic computation.

How do I install Audit Mathematical Vocabulary in Claude Code?

Run `npx skills add morluto/jacobian --skill audit-mathematical-vocabulary -a claude-code`. Or copy the skill folder (.agents/skills/audit-mathematical-vocabulary in morluto/jacobian) into .claude/skills/audit-mathematical-vocabulary in your project. Claude Code loads it when a task matches its description.

How do I install Audit Mathematical Vocabulary in Codex?

Run `npx skills add morluto/jacobian --skill audit-mathematical-vocabulary -a codex`. Or copy the skill folder (.agents/skills/audit-mathematical-vocabulary in morluto/jacobian) into .agents/skills/audit-mathematical-vocabulary in your project. Codex loads it when a task matches its description.

Can I use Audit Mathematical Vocabulary 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 morluto/jacobian --skill audit-mathematical-vocabulary -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-mathematical-vocabulary, .gemini/skills/audit-mathematical-vocabulary, .github/skills/audit-mathematical-vocabulary and .opencode/skills/audit-mathematical-vocabulary in your project.

What does Audit Mathematical Vocabulary need to run?

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

Does Audit Mathematical Vocabulary 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 Audit Mathematical Vocabulary 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 Audit Mathematical Vocabulary use?

Audit Mathematical Vocabulary is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Audit Mathematical Vocabulary use?

About 1.5k tokens (SKILL.md is roughly 6k 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 Audit Mathematical Vocabulary?

Skills that share tags, products or a category with Audit Mathematical Vocabulary: Research Refine (zjYao36/Auto-Research-Refine, 128 stars), Read GitHub (AgentTeam-TaichuAI/ScienceClaw, 671 stars), Proof Run Orchestrator (wanshuiyin/Auto-claude-code-research-in-sleep, 17k stars) and Firstdata (MLT-OSS/FirstData, 184 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Audit Mathematical Vocabulary?

morluto (a GitHub user) maintains it in morluto/jacobian, which has 220 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.