argument-mapping

argument-mapping is a skill for Claude Code, Codex from yogsoth-ai/de-anthropocentric-research-engine. It costs 32 tokens per session (970 once invoked), scanned A, original, Apache-2.0.

A research method for breaking complex debates into claims, evidence, opposing points, and conclusions, then storing the relationships as argument graphs in a wiki.

In plain words
What is it for?
Use it to extract claims from sources, attach supporting or opposing evidence, record rebuttals, score claim strength, and create synthesis reports.
Why use it?
It makes difficult discussions easier to inspect by showing which evidence supports or challenges each claim and how strong the reasoning is.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to extract claims from sources, attach supporting or opposing evidence, record rebuttals, score claim strength, and create synthesis reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill argument-mapping
Clone the repo
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for argument-mapping

README.md
[![agentmods](https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping/github.svg)](https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping)
Your own site
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for argument-mapping

Your own site · 80×15
<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/argument-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 970 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00970
Opus 5 $0.00016 $0.00485
Sonnet 5 $0.00006 $0.00194
Haiku 4.5 $0.00003 $0.00097

Measured 8d ago against content hash 738f937f0994, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

argument-mapping scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/argument-mapping/SKILL.md · 100 lines

How it starts

The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Argument Mapping

Map argument structures for research domains. Extracts claims from sources, links supporting and opposing evidence, assesses argument strength, and synthesizes coherent positions from complex debates.

Manifest

Level Count Skills
Strategy 3 claim-extraction, evidence-linking-arg, argument-synthesis
Tactic 2 claim-decomposition, strength-assessment
SOP 6 claim-page-creation, rebuttal-documentation, evidence-attachment, strength-scoring, argument-visualization, synthesis-report

Budget Table

Metric Small Medium Large
Claims extracted 10 25 50
Evidence links created 15 40 80
Rebuttals documented 3 10 20
Strength scores assigned 10 25 50
Synthesis reports 1 3 5

Strategy Sequence (Reference, Not Prescription)

  1. claim-extraction — identify and extract claims from source material
  2. evidence-linking-arg — link evidence to claims (supporting, contradicting, qualifying)
  3. argument-synthesis — synthesize positions from the argument graph

MCP Tools Used

  • vault_search — find existing claims and evidence
  • vault_add_edge — create argument edges (supported_by, contradicts, derived_from)
  • vault_query_graph — trace argument chains
  • vault_graph_stats — assess argument coverage
  • vault_lint — validate structural integrity

Context-Management

Guiding Principles

  • Claims are atomic. Each claim page states exactly one proposition. Compound claims must be decomposed.
  • Evidence is typed. Every evidence link specifies its relationship: supports, contradicts, qualifies, or is irrelevant.
  • Strength is earned. A claim's strength comes from the weight and diversity of its evidence, not from authority or repetition.
  • Steel-man first. Before documenting rebuttals, ensure the strongest version of each claim is represented.
  • Synthesis is not averaging. The synthesis report identifies which claims survive scrutiny, not a compromise between all positions.

Read the full file on GitHub · 100 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 100 lines · 32 tokens per session scan A 738f937f0994

Subscribe to this mod's changes

argument-mapping is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (462 stars, last pushed 2d ago), licensed Apache-2.0. It adds 32 tokens to every session and 970 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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