Agent skill

Doc2math

by sickn33 in sickn33/agentic-awesome-skills

Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.

MITAuto-check passed

Install Doc2math

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill doc2math -a claude-code

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

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills doc2math --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/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doc2math .claude/skills/doc2math && 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
doc2math
GitHub stars
47k
Used in
1 other repo
Token cost
~995 tokens
SKILL.md length
359 words
Files
1
Skills in repo
1,394
Repo updated
First seen
Licence
MIT

At a glance

Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.

  • Works in 5 steps: Receive Document → Classify → Extract MPS Components → …
  • SKILL.md covers When to Use This Skill, Zero-Inference Protocol…, Limitations and How It Works, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Doc2math is an agent skill from sickn33/agentic-awesome-skills. Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.

Its SKILL.md is about 1000 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

Example prompts

  • “/doc2math”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Receive Document
  2. Classify
  3. Extract MPS Components
  4. Surface Missing Information
  5. Validate and Score

What it can do on your machine

Read from SKILL.md and the folder at commit 1e53ce2. 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

    Links to these hosts (documentation or services it may open):

    • github.com
    • ace-license-server-production.up.railway.app
    • intuitek.ai

    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

Doc2math loads about 995 tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 359 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~995

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 sickn33/agentic-awesome-skills at commit 1e53ce2, republished under its MIT licence (© sickn33). 359 words, ~995 tokens.

Download SKILL.mdSave it as .claude/skills/doc2math/SKILL.md (or your agent's skills folder).
name
doc2math
description
Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.
risk
safe
source
community
date_added
2026-05-31

DOC2MATH — Document-to-Mathematics Problem Specification

When to Use This Skill

  • "Formalize this problem statement into math"
  • "Extract the mathematical structure from this research paper section"
  • "What variables, constraints, and objectives are in this spec?"
  • "Convert this word problem to a structured MPS"
  • "Find what's missing in this problem formulation"

Zero-Inference Protocol (Mandatory)

  1. Closed World — if it is not stated in the document, it does not exist in output
  2. Grounding Rule — every element must cite the exact source phrase ("evidence" field)
  3. No Silent Filling — unknown values use null; ambiguous types use "ambiguous"
  4. Inference Tagging — structural inferences tagged "inferred": true with "inference_basis"
  5. MISSING Markers — elements mentioned but insufficiently defined get "status": "MISSING" with "missing_reason"
  6. No Hallucinated Math — never introduce equations or values not in the source text

Limitations

  • Does not invent missing equations, domains, values, or assumptions that are absent from the source document.
  • Requires enough source text to cite every extracted element; sparse prompts should be returned with explicit missing-information markers.
  • Produces a formal specification, not a solved optimization model or proof.

How It Works

Step 1 — Receive Document

Accept the document text, research excerpt, problem description, or specification as input.

Step 2 — Classify

Identify problem_class: optimization | classification | simulation | proof | estimation | other

Show full SKILL.md (153 more words)Show less
Step 3 — Extract MPS Components

Variables — id, name, symbol, type, domain, units, role, evidence, inferred, status

Operators — id, name, symbol, arity, acts_on, produces, evidence, inferred

Constraints — id, type, expression, variables_involved, evidence, hardness, inferred, status

Objectives — id, direction (minimize/maximize/satisfy/find/prove), expression, variables_involved, evidence, inferred

Uncertainty — id, type (stochastic/epistemic/measurement/model/none_stated), affects, characterization, evidence, status

Step 4 — Surface Missing Information

Identify what the document implies but doesn't state: missing_information[] with element, needed_for, missing_reason.

Step 5 — Validate and Score

validation_flags:

  • has_complete_objectives: true/false/partial
  • has_bounded_variables: true/false/partial
  • has_evidence_for_all_elements: true/false/partial
  • inference_count: integer
  • missing_count: integer
  • overall_formalizability: HIGH/MEDIUM/LOW

Output Format

Produce the complete MPS as a JSON object:

json
{
  "mps_version": "1.0",
  "source_title": "...",
  "problem_class": "optimization",
  "variables": [...],
  "operators": [...],
  "constraints": [...],
  "objectives": [...],
  "uncertainty": [...],
  "missing_information": [...],
  "validation_flags": {
    "overall_formalizability": "HIGH"
  }
}

Best Practices

  • ✅ Apply all 6 Zero-Inference Protocol rules before outputting any element
  • ✅ Surface MISSING markers rather than silently inferring — incomplete formalization is valid output
  • ✅ Cite the exact source phrase in every evidence field
  • ❌ Never introduce mathematical relationships not grounded in the source text

Additional Resources

© sickn33, 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 skills/doc2math of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 1e53ce2

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Doc2math 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.

Doc2math compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Doc2math this skillsickn33/agentic-awesome-skills47k1 repos~995Automated safety check: PassMIT
Convertremotion-dev/remotion62k—~247Automated safety check: PassCustom licence
Is This A Problemanthropics/claude-for-legal9.6k2 repos~2.3kAutomated safety check: PassApache-2.0
Team NarrativeDonchitos/Claude-Code-Game-Studios26k—~4.5kAutomated safety check: PassMIT
Grounded CitationsNousResearch/hermes-agent252k—~3.1kAutomated safety check: PassMIT
Word to Markdown Convertergithub/awesome-copilot40k—~1.6kAutomated safety check: PassMIT

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Questions about Doc2math

What does Doc2math do?

Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty. Doc2math is an agent skill from sickn33/agentic-awesome-skills. Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.

How do I install Doc2math in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill doc2math -a claude-code`. Or copy the skill folder (skills/doc2math in sickn33/agentic-awesome-skills) into .claude/skills/doc2math in your project. Claude Code loads it when a task matches its description.

How do I install Doc2math in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill doc2math -a codex`. Or copy the skill folder (skills/doc2math in sickn33/agentic-awesome-skills) into .agents/skills/doc2math in your project. Codex loads it when a task matches its description.

Can I use Doc2math 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 sickn33/agentic-awesome-skills --skill doc2math -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doc2math, .gemini/skills/doc2math, .github/skills/doc2math and .opencode/skills/doc2math in your project.

What does Doc2math need to run?

SKILL.md names no scripts, command-line tools or credentials: Doc2math is instructions for the agent only.

Does Doc2math access the network?

SKILL.md names 3 domains. As links in the text: github.com, ace-license-server-production.up.railway.app and intuitek.ai. This is read from the text; nothing was executed.

Is Doc2math 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 Doc2math use?

Doc2math 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 Doc2math use?

About 995 tokens (SKILL.md is roughly 4k 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 Doc2math?

Skills that share tags, products or a category with Doc2math: Convert (remotion-dev/remotion, 62k stars), Is This A Problem (anthropics/claude-for-legal, 9.6k stars), Team Narrative (Donchitos/Claude-Code-Game-Studios, 26k stars) and Grounded Citations (NousResearch/hermes-agent, 252k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Doc2math?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,304 GitHub stars. The repository holds 1,394 skills in this directory. The repository was last updated on October 6, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.