tech-evaluation

tech-evaluation is a skill for Claude Code, Codex from pantheon-org/tekhne. It costs 193 tokens per session (1,908 once invoked), scanned A, original, MIT.

A research and decision-record tool for evaluating a library, dependency, or file format against a fixed set of questions. It produces one evidence-backed recommendation, such as adopt, reject, or keep the current choice.

In plain words
What is it for?
Use it to investigate whether a package, dependency, or file format fits a project and record the final recommendation.
Why use it?
It replaces informal technology choices with a documented finding supported by cited evidence. Structured validation helps keep the result complete and consistent.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to investigate whether a package, dependency, or file format fits a project and record the final recommendation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pantheon-org/tekhne/tech-evaluation
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 pantheon-org/tekhne --skill tech-evaluation
Clone the repo
git clone --depth 1 https://github.com/pantheon-org/tekhne

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 tech-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/pantheon-org/tekhne/tech-evaluation/github.svg)](https://agentmods.dev/skills/pantheon-org/tekhne/tech-evaluation)
Your own site
<a href="https://agentmods.dev/skills/pantheon-org/tekhne/tech-evaluation"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/tech-evaluation/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 tech-evaluation

Your own site · 80×15
<a href="https://agentmods.dev/skills/pantheon-org/tekhne/tech-evaluation"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/tech-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 193 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,908 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 120
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 $0.00193 $0.01908
Opus 5 $0.00097 $0.00954
Sonnet 5 $0.00039 $0.00382
Haiku 4.5 $0.00019 $0.00191

Measured 9d ago against content hash fb1d4ee763ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

tech-evaluation 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 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate-tech-evaluation.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/project-mgmt/tech-evaluation/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tech Evaluation

Investigate a candidate library, dependency, or file format against a fixed question set, and end with exactly one verifiable recommendation -- never "it depends." A production decision recorded without cited evidence is a guess, not a finding; this skill exists to close that gap. Produces a schema-validated structured record plus a human-readable write-up in the project's dated findings directory (see Finding Record Layout for the exact path and shape).

Prerequisites

  • A concrete technology to evaluate (an npm package, a file format, a spec) and, ideally, the alternatives already ruled out or being compared against.
  • This skill REQUIRES the create-context-file skill to persist the human-readable finding, and the context-index skill to regenerate the index afterwards -- do not run this evaluation if neither is available in the current environment.
  • A subagent capable of both web research and reading this repository's own source (to check integration/bundling fit against real code, not just documentation).

Mindset

A verdict without a cited source is a guess, not a finding -- the schema enforces at least one piece of evidence per question for exactly this reason. needs_more_research is a legitimate recommendation when the evidence is genuinely inconclusive, but it MUST NEVER be used to avoid picking a side when the evidence already points one way. One recommendation, not a comparison table with no conclusion: the point of this skill is to convert "it depends" into a decision someone can act on in production.

When to Use

  • Choosing between candidate crates/dependencies for a specific integration point (e.g. a CLI-parser decision such as usage/usage-rs vs. clap, recorded in a dated plan under .context/plans/).
  • A plan or ADR decision hinges on a factual claim about a library that keeps getting revisited because nobody wrote the answer down with evidence.
  • The user explicitly asks to "investigate," "research," or "properly evaluate" a technology option mid-decision.

Read the full file on GitHub · 139 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. 9d ago First seen · 139 lines · 193 tokens per session scan A fb1d4ee763ad

Subscribe to this mod's changes

tech-evaluation is a skill published in the GitHub repository pantheon-org/tekhne (10 stars, last pushed yesterday), licensed MIT. It adds 193 tokens to every session and 1,908 once invoked, about $0.0010 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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