Agent skill

Human Summary

by frenzymath in frenzymath/Danus

Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem.

Apache-2.0Auto-check passedDocuments & Office

Install Human Summary

skills CLI
$ npx skills add frenzymath/Danus --skill human-summary -a claude-code

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

GitHub CLI
$ gh skill install frenzymath/Danus human-summary --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/human-summary .claude/skills/human-summary && 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
human-summary
GitHub stars
476
Token cost
~1.7k tokens
SKILL.md length
827 words
Files
11
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem.

  • Works in 3 steps: generate the clean report.md (the tool… → render the PDF and deliver → backstop self-check (documented, kept as…
  • Tasks that involve PDF
  • SKILL.md covers Step 1 — generate the clean…, Step 2 — render the PDF and…, Step 3 — backstop self-check… and What the report is (locked…, plus 2 more sections
  • Runs Shell and JavaScript scripts from its folder; calls bash

What it does

Human Summary is an agent skill from frenzymath/Danus. Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem. This is NOT elaboration (the internal strategy synthesis) and NOT the dashboard. Render from the fact graph's verified statements/proofs into a clean, self-contained report — precise problem statement, essential partial results with REAL proof sketches, the one major obstacle, a neutral approach timeline, and the single remaining lemma written out in full — then output a…

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files (for example `doctor.sh`, `examples/README.md` and `examples/odd-sum/PROBLEM.md`).

It sits in Documents & Office, covering PDF. The repository describes itself as: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve PDF

Example prompts

  • “/human-summary”

Requirements

  • Node.js
  • A Bash shell

Workflow steps

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

  1. generate the clean report.md (the tool does the writing)
  2. render the PDF and deliver
  3. backstop self-check (documented, kept as defence-in-depth)

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

    Ships script files (Shell and JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • bash

    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

Human Summary loads about 1.7k tokens when it runs. Until then it costs about 136 tokens; SKILL.md has 827 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~136
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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). 827 words, ~1,717 tokens.

Download SKILL.mdSave it as .claude/skills/human-summary/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
human-summary
description
Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem. This is NOT `elaboration` (the internal strategy synthesis) and NOT the dashboard. Render from the fact graph's verified statements/proofs into a clean, self-contained report — precise problem statement, essential partial results with REAL proof sketches, the one major obstacle, a neutral approach timeline, and the single remaining lemma written out in full — then output a compiled PDF.

Human-readable progress report

You are the main agent. This skill produces a human-facing math report — for the operator, or the mathematician who posed the problem. The audience is a mathematician fluent in standard English math terminology who knows nothing about how the work was produced.

You do not author the prose yourself and you do not read the fact files. The report is written by an isolated report-writer codex behind the human-summary MCP tool, which is fed ONLY the verbatim problem statement and a scrubbed, id-free bundle of the project's verified results. That isolation is the structural guarantee that no internal identifier (fact_id, author, predecessors, …) or system/orchestration vocabulary can reach the report — the author's window never contains any of it. Your job is to call the tool, then render and deliver the PDF.

Step 1 — generate the clean report.md (the tool does the writing)

Call the MCP tool (server human-summary):

summary_write(project="<project>")

It assembles the writer prompt + PROBLEM.md + a scrubbed fact bundle (statement / proof / intuition bodies only — all frontmatter stripped, no fact ids, no author names, no machinery), drives an isolated codex, writes the result to <project>/report/report.md, and runs a leak check on the output. It returns a small dict:

{report_md_path, status, returncode, leak_findings, stderr_tail}

Honesty gate — do not proceed unless status == "ok":

  • status == "ok" means: codex exited 0, produced a non-empty report, AND the leak check found zero hits (leak_findings == []). Only then does report.md exist as a clean artifact.
  • status != "ok" (error / timeout / leak): no clean report.md is written. On a leak, the offending output is quarantined at report.leaky.md and leak_findings names what leaked — report this to the operator, do NOT render or deliver it, and do NOT hand-fix and pass it off as clean. If codex failed, surface stderr_tail.

You never read the fact graph and never write the report prose; the tool owns both. If the operator asks for a different language/register, that is a property of the writer prompt (agents/skills/human-summary/REPORT_WRITER_PROMPT.md, operator-editable) — the register rule (narrative in the operator's language, all standard math terminology in English) and the five-section structure are locked there, not here.

Step 2 — render the PDF and deliver

Once you have a clean report.md, render it to a self-contained PDF:

bash
bash "${CLAUDE_SKILL_DIR}/render_pdf.sh" <report.md> <out.pdf> "Title"

This server-renders markdown + KaTeX into self-contained HTML and prints it to PDF via headless Chrome — so the math + fonts are handled without any LaTeX engine. Deliver the PDF path to the operator — never paste raw $...$/\boxed{} into chat; it shows as tex garbage and is unreadable.

Step 3 — backstop self-check (documented, kept as defence-in-depth)

The tool's leak check is the primary guard, and the scrub makes a leak structurally impossible. As a belt-and-braces backstop before you deliver, you may still grep the rendered source:

bash
grep -E '[0-9a-f]{16}' <report.md>    # must return nothing (no fact_id / hash prefix)

If this (or the tool's leak_findings) ever fires, treat the report as compromised: do not deliver it, and report the finding.

Show full SKILL.md (362 more words)Show less

What the report is (locked spec, enforced in the writer prompt)

For reference — you do not enforce these, the isolated writer does:

  1. Register / language. Narrative in the operator's language; ALL standard math terminology stays in English (reduction, coboundary, full-rank, saturation, negative twist, Green–Griffiths, …). Math is identical across language versions; only the prose language changes.
  2. No identifiers / hashes anywhere — results are rendered as statements, not pointed at by id.
  3. Content focus: the essential partial results (each with a REAL, detailed proof sketch) + the one major obstacle; omit resolved-worry episodes.
  4. Fully self-contained statements — every object introduced, every hypothesis quantified, every symbol defined.
  5. Five sections: precise problem statement · main mathematical progress (proven / conditional) · main obstacle · neutral approach timeline · current status & the single remaining lemma written out in full (boxed).
  6. No numerical examples; honest proven / conditional / conjecture marking.
  7. No system / operational info — reads as a clean standalone research report; no fact counts, no master_guidance, no swarm/worker/verifier vocabulary, blank author, no run timestamps.

How this differs from elaboration

elaborationhuman-summary
audiencethe main agent (internal strategy)a human mathematician
densitymaximal, terse, status tablesreadable prose + detailed proof sketches
idscites fact_idsnone
lengthtightas long as the math needs (multi-page is normal)
outputa global-memory entry (kind elaboration)a compiled PDF

Run human-summary on demand (the operator asks for a report) or periodically as an operator update — it is separate from the internal strategy cycle, and it never feeds internal strategy nor reads/writes global memory as truth. It is also NOT write-paper: no bibliography, no external_refs, no house style — a private progress report, not a publication artifact.

Prerequisites for the render (declare them; the ops layer provisions them)

  • A headless Chrome / Chromium binary — resolved via DANUS_CHROME_BIN (from scripts/env.sh) or a google-chrome on PATH. This is a local PDF-render binary only; it is unrelated to any browser transport. Confirm with bash "${CLAUDE_SKILL_DIR}/doctor.sh".
  • node (provisioned by scripts/bootstrap.sh) + the pinned node deps (markdown-it, katex) in package.json. render_pdf.sh installs them once if absent; the KaTeX CSS is then vendored from the local install, so subsequent renders need no network.

A tiny 3-fact example under examples/ exercises the render pipeline end to end.

© 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 10 other files in .agents/skills/human-summary of frenzymath/Danus.

  • SKILL.md
  • doctor.sh
  • examples/README.md
  • examples/odd-sum/PROBLEM.md
  • examples/odd-sum/fact_graph/facts/fact_odd_recurrence.md
  • examples/odd-sum/fact_graph/facts/fact_odd_sum_main.md
  • examples/odd-sum/fact_graph/facts/fact_square_recurrence.md
  • examples/report.md
  • md2html.js
  • package.json
  • render_pdf.sh

Open the folder on GitHubat commit 6d92e8d

Compare with similar skills

Human Summary 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.

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Human Summary this skillfrenzymath/Danus476—~1.7kAutomated safety check: PassApache-2.0
MarkitdownImCa0/just-laws78214 repos~3.2kAutomated safety check: NotesMIT
Gzh Designisjiamu/gzh-design-skill3.9k1 repos~2.2kAutomated safety check: PassAGPL-3.0
GenOffice Document CLIgenspark-ai/genoffice9k—~19kAutomated safety check: PassApache-2.0
Harness Book Best Practicewquguru/harness-books3.2k—~4.1kAutomated safety check: PassNone
Bookforge Korean Ebook PDF Makergongnyang/bookforge3151 repos~1.7kAutomated safety check: PassMIT

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Questions about Human Summary

What does Human Summary do?

Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem. Human Summary is an agent skill from frenzymath/Danus. Write a human-readable mathematical progress report (compiled PDF) on a project for the operator / the mathematician who posed the problem.

When should I use Human Summary?

Human Summary fits situations like: tasks that involve PDF.

How do I install Human Summary in Claude Code?

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

How do I install Human Summary in Codex?

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

Can I use Human Summary 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 human-summary -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/human-summary, .gemini/skills/human-summary, .github/skills/human-summary and .opencode/skills/human-summary in your project.

What does Human Summary need to run?

Going by SKILL.md and its folder, Human Summary needs a shell and JavaScript for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: Node.js; A Bash shell.

Does Human Summary 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 Human Summary 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 Human Summary use?

Human Summary 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 Human Summary use?

About 1.7k tokens (SKILL.md is roughly 6.9k 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 Human Summary?

Skills that share tags, products or a category with Human Summary: Markitdown (ImCa0/just-laws, 782 stars), Gzh Design (isjiamu/gzh-design-skill, 3.9k stars), GenOffice Document CLI (genspark-ai/genoffice, 9k stars) and Harness Book Best Practice (wquguru/harness-books, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Human Summary?

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.