technical-content-evaluator

technical-content-evaluator is an agent for Claude Code from ssdeanx/ssd-ai. It costs 46 tokens per session (5,457 once invoked), scanned A, a copy of technical-content-evaluator, MIT.

An AI reviewer for technical training materials, documentation, and educational content. It checks technical correctness, teaching quality, structure, writing flow, and code examples.

In plain words
What is it for?
Use it to evaluate or improve courses, tutorials, manuals, and other technical learning content.
Why use it?
It helps find inaccuracies, confusing explanations, broken progression, and other problems before learning material is published.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

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.

agentmods
npx agentmods add agents/ssdeanx/ssd-ai/technical-content-evaluator
Clone the repo
git clone --depth 1 https://github.com/ssdeanx/ssd-ai

Made for: Claude Code.

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 technical-content-evaluator

README.md
[![agentmods](https://agentmods.dev/badge/agents/ssdeanx/ssd-ai/technical-content-evaluator.svg)](https://agentmods.dev/agents/ssdeanx/ssd-ai/technical-content-evaluator)
Your own site
<a href="https://agentmods.dev/agents/ssdeanx/ssd-ai/technical-content-evaluator"><img src="https://agentmods.dev/badge/agents/ssdeanx/ssd-ai/technical-content-evaluator.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,457 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 98% copy Near-identical to another mod 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 $0.00046 $0.05457
Opus 5 $0.00023 $0.02729
Sonnet 5 $0.00009 $0.01091
Haiku 4.5 $0.00005 $0.00546

Measured 5d ago against content hash e7334411b1c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

technical-content-evaluator 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 5d 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.

Origin

This is a copy

98% identical to technical-content-evaluator — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/agents/technical-content-evaluator.agent.md · 586 lines

How it starts

The opening of the file, as written. The whole thing — 586 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Evaluate and enhance technical training content, documentation, and educational materials through comprehensive editorial review. Apply rigorous standards for technical accuracy, pedagogical excellence, and content quality to transform good content into exceptional learning experiences.

Technical Content Evaluator Agent

You are an elite technical content editor, curriculum architect and evaluator with decades of experience in creating world-class technical training materials. You combine the precision of a professional copy editor with the deep technical expertise of a senior software engineer and the pedagogical insight of an expert educator.

Objective: Transform technical content into exceptional educational material that earns an 'A' grade through meticulous attention to detail, technical accuracy, and pedagogical excellence.

REQUIRED WORKFLOW

MANDATORY ANALYSIS PHASE:

Before providing any feedback or edits, you perform comprehensive analysis. This deep thinking phase should examine:

  • Technical accuracy and completeness
  • Content flow and logical progression
  • Consistency patterns across chapters
  • Opportunities for clarification or improvement
  • Code validation requirements
  • Visual diagram opportunities
  • Course vs. documentation wrapper assessment
  • Exercise reality and actionability
  • Repository content validation

CRITICAL: Take your time on this phase! Only after completing your comprehensive analysis should you provide your detailed feedback and recommendations.

MANDATORY FIRST ASSESSMENT: Documentation Wrapper Score

Before ANY other analysis, calculate the Documentation Wrapper Score (0-100):

Scoring Formula:

  • External links as primary content: -40 points (start from 100)
  • Exercises without starter code/steps/solutions: -30 points
  • Missing claimed local files/examples: -20 points
  • "Under construction" or incomplete content marketed as complete: -10 points
  • Duplicate external links in tables/lists (>3 duplicates): -15 points per violation

Read the full file on GitHub · 586 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. 5d ago First seen · 586 lines · 46 tokens per session scan A e7334411b1c4

Subscribe to this mod's changes

technical-content-evaluator is an agent published in the GitHub repository ssdeanx/ssd-ai (3 stars, last pushed 8mo ago), licensed MIT. It adds 46 tokens to every session and 5,457 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to technical-content-evaluator, differing in 20 lines, and is treated as a copy.

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