tech-research

tech-research is a skill for Claude Code, Codex from jamestorrevillas/dev-skills. It costs 68 tokens per session (751 once invoked), scanned A, original, MIT.

A guide for researching technologies and making technical choices, such as comparing frameworks or deciding whether to build a tool or buy one.

In plain words
What is it for?
Use it to evaluate problem fit, maturity, community, maintenance, performance, learning effort, ecosystem, migration difficulty, and software licensing.
Why use it?
It helps replace guesswork with a defined decision, comparable criteria, reliable sources, and documented reasoning.

Skill for Claude CodeCodex

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

Good fit Use it to evaluate problem fit, maturity, community, maintenance, performance, learning effort, ecosystem, migration difficulty, and software licensing.

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

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-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/jamestorrevillas/dev-skills/tech-research.svg)](https://agentmods.dev/skills/jamestorrevillas/dev-skills/tech-research)
Your own site
<a href="https://agentmods.dev/skills/jamestorrevillas/dev-skills/tech-research"><img src="https://agentmods.dev/badge/skills/jamestorrevillas/dev-skills/tech-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 751 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.
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 $0.00068 $0.00751
Opus 5 $0.00034 $0.00376
Sonnet 5 $0.00014 $0.00150
Haiku 4.5 $0.00007 $0.00075

Measured 8d ago against content hash 3c6674fe05db, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

tech-research 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.

.github/skills/tech-research/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Technology Research

Research Process

1. DEFINE    — What specific decision are we making?
2. CONSTRAIN — What are the non-negotiables? (team skills, budget, timeline)
3. GATHER    — Collect data from quality sources
4. COMPARE   — Evaluate options against the same criteria
5. DECIDE    — Choose with explicit reasoning
6. DOCUMENT  — Record the decision for future reference

Technology Evaluation Criteria

Criterion What to Look For
Problem Fit Does it actually solve YOUR problem?
Maturity Production-proven? Version 1.x or 0.x?
Community Active GitHub, Stack Overflow, Discord
Maintenance Last commit? Open issues? Response time?
Performance Benchmarks relevant to your scale
Learning Curve Team familiarity, documentation quality
Ecosystem Plugins, integrations, tooling
Exit Cost How hard to migrate away?
License MIT/Apache (permissive) vs GPL vs commercial

Source Quality Hierarchy

  1. Official documentation — authoritative, check version
  2. Production case studies — most reliable, hardest to find
  3. Benchmark comparisons — verify the benchmark matches your use case
  4. Respected technical blogs — check date and author credentials
  5. Reddit / Hacker News — good for real-world sentiment and gotchas
  6. YouTube tutorials — useful for learning, not for decisions

Always check the date. A 2-year-old comparison may be obsolete.


Decision Document Template

## Technology Decision: [topic]

**Date:** | **Decided by:**

### Context
[What problem are we solving? What are our constraints?]

### Options Evaluated
| Criterion | Option A | Option B | Option C |
|-----------|---------|---------|---------|
| Problem Fit | | | |
| Maturity | | | |
| Team Familiarity | | | |
| Performance | | | |
| Long-term Risk | | | |

### Decision
**Chosen:** [option]

**Reasoning:** [why this fits our specific context]

**Trade-offs accepted:** [what we give up]

**Revisit if:** [conditions that would change this decision]

Read the full file on GitHub · 107 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 · 107 lines · 0 tokens per session scan A 3c6674fe05db

Subscribe to this mod's changes

tech-research is a skill published in the GitHub repository jamestorrevillas/dev-skills (3 stars, last pushed 5mo ago), licensed MIT. It adds 68 tokens to every session and 751 once invoked, about $0.0003 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 2026-08-31.

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