argumentation

argumentation is a skill for Claude Code from pjt222/agent-almanac. It costs 86 tokens per session (3,678 once invoked), scanned A, original, MIT.

A method for building clear arguments from a claim, the reasoning behind it, and concrete examples or evidence. It also considers and strengthens opposing viewpoints.

In plain words
What is it for?
Use it for pull request descriptions, architecture decisions, code reviews, research writing, and technical proposals.
Why use it?
It prevents technical explanations from resting on unsupported opinions or unclear logic.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the agent-almanac plugin — 122 skills, 76 agents shipped together

Good fit Use it for pull request descriptions, architecture decisions, code reviews, research writing, and technical proposals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pjt222/agent-almanac/argumentation
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 pjt222/agent-almanac --skill argumentation
Clone the repo
git clone --depth 1 https://github.com/pjt222/agent-almanac

Made for: Claude Code.

Or install agent-almanac, the plugin that ships this one along with the rest of its 122 skills, 76 agents.

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 argumentation

README.md
[![agentmods](https://agentmods.dev/badge/skills/pjt222/agent-almanac/argumentation.svg)](https://agentmods.dev/skills/pjt222/agent-almanac/argumentation)
Your own site
<a href="https://agentmods.dev/skills/pjt222/agent-almanac/argumentation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/argumentation.svg" alt="Measured on agentmods" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,678 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 $0.00086 $0.03678
Opus 5 $0.00043 $0.01839
Sonnet 5 $0.00017 $0.00736
Haiku 4.5 $0.00009 $0.00368

Measured 4d ago against content hash 9f585d1d3a1e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

argumentation 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 4d 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.

i18n/caveman-lite/skills/argumentation/SKILL.md · 258 lines

How it starts

The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Construct Arguments

Build rigorous arguments from hypothesis through reasoning to concrete evidence. Every persuasive technical claim follows the same triad: a clear hypothesis states what you believe, an argument explains why it holds, and examples prove that it holds. This skill teaches you to apply that structure to code reviews, design decisions, research writing, and any context where claims need justification.

When to Use

  • Writing or reviewing a PR description that proposes a technical change
  • Justifying a design decision in an ADR (Architecture Decision Record)
  • Constructing feedback in a code review that goes beyond "I don't like this"
  • Writing a research argument or technical proposal
  • Challenging or defending an approach in a technical discussion

Inputs

  • Required: A claim or position that needs justification
  • Required: Context (code review, design decision, research, documentation)
  • Optional: Audience (peer developers, reviewers, stakeholders, researchers)
  • Optional: Counterarguments or alternative positions to address
  • Optional: Evidence or data available to support the claim

Procedure

Step 1: Formulate the Hypothesis

State your claim as a clear, falsifiable hypothesis. A hypothesis is not an opinion or a preference -- it is a specific assertion that can be tested against evidence.

  1. Write the claim in one sentence
  2. Apply the falsifiability test: can someone prove this wrong with evidence?
  3. Scope it narrowly: constrain to a specific context, codebase, or domain
  4. Distinguish from opinions by checking for testable criteria

Falsifiable vs. unfalsifiable:

Unfalsifiable (opinion) Falsifiable (hypothesis)
"This code is bad" "This function has O(n^2) complexity where O(n) is achievable"
"We should use TypeScript" "TypeScript's type system will catch the class of null-reference bugs that caused 4 of our last 6 production incidents"
"The API design is cleaner" "Replacing the 5 endpoint variants with a single parameterized endpoint reduces the public API surface by 60%"
"This research approach is better" "Method A achieves higher precision than Method B on dataset X at the 95% confidence level"

Read the full file on GitHub · 258 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. 4d ago First seen · 258 lines · 86 tokens per session scan A 9f585d1d3a1e

Subscribe to this mod's changes

argumentation is a skill published in the GitHub repository pjt222/agent-almanac (32 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 3,678 once invoked, about $0.0004 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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