research-first

research-first is a skill for Codex from ZaxbyHub/opencode-swarm. It costs 52 tokens per session (177 once invoked), scanned A, original, MIT.

A research-before-planning workflow for coding tasks that depend on current facts, unfamiliar tools, standards, security notices, or repository behavior.

In plain words
What is it for?
Use it to check external documentation, release notes, security advisories, APIs, libraries, or local code before deciding how to implement a change.
Why use it?
It reduces the risk of planning from outdated, guessed, or unverified information.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: reads .claude/ paths; installed under .agents/ (shared by several agents); mentions Codex.

Good fit Use it to check external documentation, release notes, security advisories, APIs, libraries, or local code before deciding how to implement a change.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zaxbyhub/opencode-swarm/research-first
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 ZaxbyHub/opencode-swarm --skill research-first
Clone the repo
git clone --depth 1 https://github.com/ZaxbyHub/opencode-swarm

Made for: 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 research-first

README.md
[![agentmods](https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/research-first.svg)](https://agentmods.dev/skills/zaxbyhub/opencode-swarm/research-first)
Your own site
<a href="https://agentmods.dev/skills/zaxbyhub/opencode-swarm/research-first"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/research-first.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 177 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 Agent Snooping · line 9
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 $0.00052 $0.00177
Opus 5 $0.00026 $0.00088
Sonnet 5 $0.00010 $0.00035
Haiku 4.5 $0.00005 $0.00018

Measured 8d ago against content hash 25a795386870, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

research-first 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.

.agents/skills/research-first/SKILL.md · 19 lines

What it actually says

Research First

Read .claude/skills/research-first/SKILL.md for the source protocol.

Codex-specific execution notes:

  • For current or unstable external facts, browse or use primary sources and cite URLs.
  • For repo facts, prefer rg, file reads, tests, and local source over memory.
  • Separate verified facts from assumptions.
  • Do not plan implementation until the relevant unknowns are resolved or explicitly marked as risks.

When research affects OpenAI product usage, use the openai-docs skill and official sources only.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 19 lines · 52 tokens per session scan A 25a795386870

Subscribe to this mod's changes

research-first is a skill published in the GitHub repository ZaxbyHub/opencode-swarm (463 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 177 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 2026-08-30.