research-ops

research-ops is a skill for Claude Code, Codex from 23ag1/completely. It costs 39 tokens per session (759 once invoked), scanned A, a copy of research-ops, MIT.

A workflow for researching current facts, comparing options, enriching company or people information, and making evidence-based recommendations. It can combine web discovery, multi-source research, market analysis, and saved knowledge when relevant.

In plain words
What is it for?
Use it for current research, comparisons, company or people enrichment, recommendations, and ongoing information monitoring.
Why use it?
It provides a repeatable way to gather fresh public evidence instead of relying on memory or isolated searches. It also helps turn recurring research into a monitored process.

Skill for Claude CodeCodex

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 skills/23ag1/completely/research-ops
Any agent
npx skills add 23ag1/completely --skill research-ops
Clone the repo
git clone --depth 1 https://github.com/23ag1/completely

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 research-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/23ag1/completely/research-ops.svg)](https://agentmods.dev/skills/23ag1/completely/research-ops)
Your own site
<a href="https://agentmods.dev/skills/23ag1/completely/research-ops"><img src="https://agentmods.dev/badge/skills/23ag1/completely/research-ops.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 759 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% 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 $0.00039 $0.00759
Opus 5 $0.00019 $0.00380
Sonnet 5 $0.00008 $0.00152
Haiku 4.5 $0.00004 $0.00076

Measured 3d ago against content hash f6006b8554c6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-ops 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 3d 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

100% identical to research-ops — 0 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.

research/ecc/skills/research-ops/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Ops

Use this when the user asks to research something current, compare options, enrich people or companies, or turn repeated lookups into a monitored workflow.

This is the operator wrapper around the repo's research stack. It is not a replacement for deep-research, exa-search, or market-research; it tells you when and how to use them together.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • exa-search for fast current-web discovery
  • deep-research for multi-source synthesis with citations
  • market-research when the end result should be a recommendation or ranked decision
  • lead-intelligence when the task is people/company targeting instead of generic research
  • knowledge-ops when the result should be stored in durable context afterward

When to Use

  • user says "research", "look up", "compare", "who should I talk to", or "what's the latest"
  • the answer depends on current public information
  • the user already supplied evidence and wants it factored into a fresh recommendation
  • the task may be recurring enough that it should become a monitor instead of a one-off lookup

Guardrails

  • do not answer current questions from stale memory when fresh search is cheap
  • separate:
    • sourced fact
    • user-provided evidence
    • inference
    • recommendation
  • do not spin up a heavyweight research pass if the answer is already in local code or docs

Workflow

1. Start from what the user already gave you

Normalize any supplied material into:

  • already-evidenced facts
  • needs verification
  • open questions

Do not restart the analysis from zero if the user already built part of the model.

2. Classify the ask

Choose the right lane before searching:

  • quick factual answer
  • comparison or decision memo
  • lead/enrichment pass
  • recurring monitoring candidate

3. Take the lightest useful evidence path first

  • use exa-search for fast discovery
  • escalate to deep-research when synthesis or multiple sources matter
  • use market-research when the outcome should end in a recommendation
  • hand off to lead-intelligence when the real ask is target ranking or warm-path discovery

Read the full file on GitHub · 113 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. 3d ago First seen · 113 lines · 39 tokens per session scan A f6006b8554c6

Subscribe to this mod's changes

research-ops is a skill published in the GitHub repository 23ag1/completely (5 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 759 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research-ops, differing in 0 lines, and is treated as a copy.